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Research Article | 20-February-2013

ADAPTIVE ESTIMATION AND PI LEARNING SPRING-RELAXATION TECHNIQUE FOR LOCATION ESTIMATION IN WIRELESS SENSOR NETWORKS

In order to reduce the location estimation error in Wireless Sensor Network(WSN). A localization algorithm is proposed combining adaptive estimation, PI-learning and spring-relaxation techniques for wireless sensor networks in this paper. Our proposed method takes the advantages of the spring-relaxation technique, thus it inherits its simplicity. The overall accuracy of the location estimations is improved by introducing adaptive estimation and PI-learning. Moreover, it requires only a few

Li Haiyan, Hu Yun-an, Zhu Min

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 1, 317–332

Research Communicate | 20-November-2017

REMARKS ON THE ESTIMATION OF POSITION PARAMETERS

The article contains some theoretical remarks about selected models of position parameters estimation as well as numerical examples of the problem. We ask a question concerning the existence of possible measures of the quality of interval estimation and we mention some popular measures applied to the task. Point estimation is insufficient in practical problems and it is rather interval estimation that is in wide use. Too wide interval suggests that the information available is not sufficient to

Czesław Domański

Statistics in Transition New Series, Volume 18 , ISSUE 3, 549–558

Article | 01-June-2016

RANDOM SIGNAL FREQUENCY IDENTIFICATION BASED ON AR MODEL SPECTRAL ESTIMATION

The power spectral estimation is an important element in the random signal analysis. The paper will introduce the principles of the classical power spectral estimation and modern power spectral estimation, analyses their characteristics and application in MATLAB simulation. The variance obtained by the classical power spectral estimation is inversely proportional to its resolution, the resolution of the modern spectral estimation are not subject to this restriction, but also the variance

Chunhuan Song

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 2, 884–908

Article | 06-July-2017

DEVELOPMENT OF SMALLAREA ESTIMATION IN OFFICIAL STATISTICS

. Next, before discussing general issues of small area estimation (SAE) in official statistics, the author reminds: the methods of sampling surveys, data collection, estimation procedures, and data quality assessment used for official statistics. Statistical information is published in different breakdowns with stable or even decreasing budget while being legally bound to control the response burden. Special attention is paid, from a practitioner point of view, to synthetic development of small area

Jan Kordos

Statistics in Transition New Series, Volume 17 , ISSUE 1, 105–132

Article | 06-July-2017

SMALL AREA ESTIMATION OF INCOME UNDER SPATIAL SAR MODEL

The paper presents the method of hierarchical Bayes (HB) estimation under small area models with spatially correlated random effects and a spatial structure implied by the Simultaneous Autoregressive (SAR) process. The idea was to improve the spatial EBLUP by incorporating the HB approach into the estimation algorithm. The computation procedure applied in the paper uses the concept of sampling from a posterior distribution under generalized linear mixed models implemented in WinBUGS software

Jan Kubacki, Alina Jędrzejczak

Statistics in Transition New Series, Volume 17 , ISSUE 3, 365–390

Article | 22-January-2018

MAPPING POVERTY AT THE LEVEL OF SUBREGIONS IN POLAND USING INDIRECT ESTIMATION

estimation methods, which rely on information from outside the subpopulation of interest, which usually increases estimation precision. The main aim of this paper is to show results of estimation of the poverty indicator at a lower level of spatial aggregation than the one used so far, that is at the level of subregions in Poland (NUTS 3) using the small area estimation methodology (SAE), i.e. a model–based technique – the EBLUP estimator based on the Fay–Herriot model. By optimally

Marcin Szymkowiak, Andrzej Młodak, Łukasz Wawrowski

Statistics in Transition New Series, Volume 18 , ISSUE 4, 609–635

Research Article | 13-December-2017

Optical Flow Algorithm for Velocity Estimation of Ground Vehicles: A Feasibility Study

This paper presents a novel velocity estimation method for all terrain ground vehicles. The technique is based on a camera that scans the ground and estimates the velocity by using an optical flow algorithm. The method is tested and validated for different types of terrains such as fine sand, coarse sand, gravel as well as a mixture of coarse sand and gravel. Measured velocities from precise encoders are compared with the velocities predicted by the optical flow algorithm, showing promising

Savan Chhaniyara, Pished Bunnun, Lakmal D. Seneviratne, Kaspar Althoefer

International Journal on Smart Sensing and Intelligent Systems, Volume 1 , ISSUE 1, –

Research Article | 27-December-2017

Extended Kalman Filtering and Pathloss modeling for Shadow Power Parameter Estimation in Mobile Wireless Communications

In this paper accurate estimation of parameters, higher order state space prediction methods and Extended Kalman filter (EKF) for modeling shadow power in wireless mobile communications are developed. Path-loss parameter estimation models are compared and evaluated. Shadow power estimation methods in wireless cellular communications are very important for use in power control of mobile device and base station. The methods are validated and compared to existing methods, Kalman Filter (KF) with

George P. Pappas, Mohamed A. Zohdy

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 2, 898–924

Article | 13-December-2019

ESTIMATION OF INCOME CHARACTERISTICS FOR REGIONS IN POLAND USING SPATIO-TEMPORAL SMALL AREA MODELS

The paper presents the comparison of estimation results for spatial and spatiotemporal small area models. The study was carried out for income-related variables drawn from the Polish Household Budget Survey and explanatory variables from the Polish Local Data Bank for the years 2003-2013. The properties of EBLUPs (Empirical Best Linear Unbiased Predictors) based on spatiotemporal models, which utilize spatial correlation between neighbouring areas as well as historical data, were compared and

Alina Jędrzejczak, Jan Kubacki

Statistics in Transition New Series, Volume 20 , ISSUE 4, 113–134

Research Article | 13-December-2017

RAILWAY WHEELSET PARAMETER ESTIMATION USING SIGNALS FROM LATERAL VELOCITY SENSOR

A type of parameter estimation technique based on the linear integral filter (LIF) method, the least-absolute error with variable forgetting factor (LAE+VFF) estimation method, is proposed in this paper to estimate the railway wheelset parameters modelled as a time-varying continuous-time (C-T) system. The inputs to the parameter estimator are the control signal and the railway wheelset system output, which is the wheelset’s lateral velocity. The algorithm includes an instrumental variable (IV

H. Selamat, A. J. Alimin, Y. M. Sam

International Journal on Smart Sensing and Intelligent Systems, Volume 1 , ISSUE 3, 754–770

Article | 06-July-2017

SMALL AREA ESTIMATION IN THE GERMAN CENSUS 2011

In 2011, Germany conducted the first census after the reunification. In contrast to a classical census, a register-assisted census was implemented using population register data and an additional sample. This paper provides an overview of how the sampling design recommendations were set up in order to fulfil legal requirements and to guarantee an optimal but still flexible source of information. The aim was to develop a design that fosters an accurate estimation of the main objective of the

Ralf Münnich, Jan Pablo Burgard, Siegfried Gabler, Matthias Ganninger, Jan-Philipp Kolb

Statistics in Transition New Series, Volume 17 , ISSUE 1, 25–40

Article | 05-September-2021

A calibrated synthetic estimator for small area estimation

relative bias and greater efficiency. Moreover, they prove more consistent than the existing classical synthetic estimator. The further evaluation carried out using the coefficient of variation provides additional confirmation of the calibrated estimator’s advantage over the existing ones in relation to small area estimation.

Matthew Joshua Iseh, Ekaette Inyang Enang

Statistics in Transition New Series, Volume 22 , ISSUE 3, 15–30

Research Article | 27-December-2017

MOVING TARGET DETECTION BASED ON GLOBAL MOTION ESTIMATION IN DYNAMIC ENVIRONMENT

AUV localization is not accurate based on sequence images if moving target is as landmark,so the moving target detection algorithm is studied based on global motion estimation, which detects and eliminates moving target according to the motion inconsistency of the moving target. Generally grid block matching is used in the global motion estimation, it can’t effectively dispose the dynamic background, and the gradient direction invariant moments descriptors method of free circular neighborhood

GAO Jun-chai, LIU Ming-yong, XU Fei

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 1, 360–379

Article | 22-January-2018

ESTIMATION OF SMALL AREA CHARACTERISTICS USING MULTIVARIATE RAO-YU MODEL

The growing demand for high-quality statistical data for small areas coming from both the public and private sector makes it necessary to develop appropriate estimation methods. The techniques based on small area models that combine time series and cross-sectional data allow for efficient "borrowing strength" from the entire population and they can also take into account changes over time. In this context, the EBLUP estimation based on multivariate Rao-Yu model, involving both

Alina Jędrzejczak, Jan Kubacki

Statistics in Transition New Series, Volume 18 , ISSUE 4, 725–742

Article | 05-June-2013

AN ESTIMATION ALGORITHM FOR MISSING DATA IN WIRELESS SENSOR NETWORKS

For estimating the missing data of wireless sensor networks, an estimation algorithm called HD method, which can make use of sensoring space-time correlation of the data, was proposed based on mathematical Hermite and DESM statistical models. The algorithm not only can adaptively adjust the time and space weights, but also can accurately estimate the missing or unavailable data. The experimental results show that the algorithm has good stability and relatively high estimation accuracy.

Nan Yan, Ming-zheng Zhou, Li Tong

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 3, 1032–1053

Article | 23-March-2018

OBJECTIFICATION OF SUBJECTIVE ESTIMATION OF ABNORMAL CASES DANGER IN AIR TRAFFIC CONTROL

In the article, the problems of objectification of the subjective danger estimation for abnormal cases in air traffic control are considered. An overview of currently existing approaches is given. In addition, the article presents the analysis of the statistical results of testing 252 air traffic controllers. This study reveals a subjective danger estimation inadequacy and its connection to air traffic controller’s potential extreme working capacity. A new approach to objectification of

Olga ARINICHEVA, Yakov DALINGER, Aleksei MALISHEVSKII, Nikolai SUKHIKH, Yurii KHOROSHAVTSEV

Transport Problems, Volume 13 , ISSUE 1, 5–18

Research paper | 01-November-2017

INFERENTIAL ISSUES IN MODEL-BASED SMALL AREA ESTIMATION: SOME NEW DEVELOPMENTS

Small area estimation (SAE) has seen a rapid growth over the past 10 years or so. Earlier work is covered in the author's book (Rao 2003). The main purpose of this paper is to highlight some new developments in model-based SAE since the publication of the author's book. A large part of the new theory addressed practical issues associated with the model-based approach, and we present some of those methods for area level and unit level models. We also briefly mention some new work on synthetic

J. N. K. Rao

Statistics in Transition New Series, Volume 16 , ISSUE 4, 491–510

Sampling Methods | 20-November-2017

ON ASYMMETRY OF PREDICTION ERRORS IN SMALL AREA ESTIMATION

The mean squared error reflects only the average prediction accuracy while the distribution of squared prediction error is positively skewed. Hence, assessing or comparing accuracy based on the MSE (which is the mean of squared errors) is insufficient and even inadequate because we should be interested not only in the average but in the whole distribution of prediction errors. This is the reason why we propose to use different than MSE measures of prediction accuracy in small area estimation

Tomasz Żądło

Statistics in Transition New Series, Volume 18 , ISSUE 3, 413–432

Research Article | 01-June-2020

Statistical properties and different methods of estimation for extended weighted inverted Rayleigh distribution

statistics have been derived. Different estimation procedures have also been discussed to estimate the unknown parameters of the proposed probability distribution. The Monte Carlo simulation study has been conducted to compare the performances of the proposed estimators obtained through various methods of estimation. Finally, two real data sets have been used to show the applicability of the proposed model in a real-life scenario.

Abhimanyu Singh Yadav, S. K. Singh, Umesh Singh

Statistics in Transition New Series, Volume 21 , ISSUE 2, 119–141

Article | 18-March-2020

Robust estimation of wages in small enterprises:  the application to Poland’s districts

The paper presents an empirical study designed to test a small area estimation method. The aim of the study is to apply a robust version of the Fay-Herriot model to the estimation of average wages in the small business sector. Unlike the classical Fay-Herriot model, its robust version makes it possible to meet the assumption of normality of random effects under the presence of outliers. Moreover, the use of this version of the Fay-Herriot model helps to improve the precision of estimates

Grażyna Dehnel, Łukasz Wawrowski

Statistics in Transition New Series, Volume 21 , ISSUE 1, 137–157

Research Article | 27-February-2017

ROAD ACCIDENT ESTIMATION MODEL IN URBAN AREAS

accidents. Using specific spatial analysis, a model of accident estimation in the urban areas of Bucharest is developed. The study aims to provide useful tools for urban decision makers for a-priori analysis of the consequences of urban outline changes on traffic risks.

Serban RAICU, Dorinela COSTESCU, Stefan BURCIU, Florin RUSCA, Mircea ROSCA

Transport Problems, Volume 11 , ISSUE 3, 33–42

Research paper | 01-November-2017

Triple-goal estimation of unemployment rates for U.S. states using the U.S. Current Population Survey data

In this paper, we first develop a triple-goal small area estimation methodology for simultaneous estimation of unemployment rates for U.S. states using the Current Population Survey (CPS) data and a two-level random sampling variance normal model. The main goal of this paper is to illustrate the utility of the triple-goal methodology in generating a single series of unemployment rate estimates for three separate purposes: developing estimates for individual small area means, producing 

Daniel Bonnéry, Yang Cheng, Neung Soo Ha, Partha Lahiri

Statistics in Transition New Series, Volume 16 , ISSUE 4, 511–522

Article | 10-April-2018

Association Rule Mining Based on Estimation of Distribution Algorithm for Blood Indices

To come over the limitations of Apriori algorithm and association rule mining algorithm based on Genetic Algorithm (GA), this paper proposed a new association rule mining algorithm based on the population-based incremental algorithm (PBIL), which is a kind of distribution estimation algorithms. The proposed association rule-mining algorithm keeps the advantages of GA mining association rules in coding and the fitness function. Through using probability vector possessing learning properties to

Xinyu Zhang, Botu Xue, Guanghu Sui, Jianjiang Cui

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 20–26

Article | 06-July-2017

INTERVAL ESTIMATION OF HIGHER ORDER QUANTILES. ANALYSIS OF ACCURACY OF SELECTED PROCEDURES

In the paper selected nonparametric and semiparametric estimation methods of higher orders quantiles are considered. The construction of nonparametric confidence intervals is based on order statistics of appropriate ranks from random samples or from generated bootstrap samples. Semiparametric bootstrap methods are characterized by double bootstrap simulations. The values of bootstrap sample below the prearranged threshold are generated by the empirical distribution and the values above this

Dorota Pekasiewicz

Statistics in Transition New Series, Volume 17 , ISSUE 4, 737–748

Research Article | 24-August-2017

MET AND UNMET NEED FOR CONTRACEPTION: SMALL AREA ESTIMATION FOR RAJASTHAN STATE OF INDIA

of unwanted births ends in childbirths, and which are related to deaths and injuries for both mother and child. Due to lack of availability of reliable data at the small level (area-wise) specifically in developing countries like India. In this article the small area estimation technique is used for the estimation of met and unmet need for contraception for 187 towns of Rajasthan state of India and for empirical analysis. Data is taken from the District Level Household Survey (DLHS): 2002-04 and

Piyush Kant Rai, Sarla Pareek, Hemlata Joshi

Statistics in Transition New Series, Volume 18 , ISSUE 2, 329–360

Article | 11-April-2018

Self-adaptive Differential Evolutionary Extreme Learning Machine and Its Application in Facial Age Estimation

-validation strategy is proposed to be embedded into the training phase so as to solve the overtraining problem. Experimental results demonstrate that the proposed algorithms are efficient for Facial Age Estimation.

Junhua Ku, Kongduo Xing

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 72–77

research-article | 30-November-2019

An incremental meter placement method for state estimation considering collinear measurements and high leverage points

The conventional state estimation (SE) is formulated as an iterative weighted least-squares (WLS) problem (Monticelli, 2000; Chakrabarti et al., 2010; Biswal et al., 2012). The WLS SE is a nonlinear regression operation that deduces the response (state variables) from the observation set (measurement set) (Liu et al., 2014). The meters that are associated with the power system SE includes synchronized phasor measurement units (PMUs) and SCADA meters. The SCADA meters which are the conventional

Hatim G. Abood, Victor Sreeram, Yateendra Mishra

International Journal on Smart Sensing and Intelligent Systems, Volume 13 , ISSUE 1, 1–12

Research paper | 31-October-2017

AN APPROXIMATION TO THE OPTIMAL SUBSAMPLE ALLOCATION FOR SMALL AREAS

This paper develops allocation methods for stratified sample surveys in which small area estimation is a priority. We assume stratified sampling with small areas as the strata. Similar to Longford (2006), we seek efficient allocation that minimizes a linear combination of the mean squared errors of composite small area estimators and of an estimator of the overall mean. Unlike Longford, we define mean-squared error in a model-assisted framework, allowing a more natural interpretation of results

W. B. Molefe, D. K. Shangodoyin, R. G. Clark

Statistics in Transition New Series, Volume 16 , ISSUE 2, 163–182

research-article | 30-November-2018

Employment of PSO algorithm to improve the neural network technique for radial distribution system state estimation

Nomenclatures SE state estimation PS power system PSN power system networks PSO–NN particle swarm optimization–neural network DPN distribution power network RDPSNs radial distribution power system networks DMS distribution management system GTP graph theoretic procedure algorithm DSSE distribution system state estimation model WLS weighted least square WLAV weighted least absolute value PMUs phasor measurement units ANN artificial neural network

Husham Idan Hussein, Ghassan Abdullah Salman, Ahmed Majeed Ghadban

International Journal on Smart Sensing and Intelligent Systems , Volume 12 , ISSUE 1, 1–10

Article | 06-July-2017

SOME EFFECTIVE ESTIMATION PROCEDURES UNDER NON-RESPONSE IN TWO-PHASE SUCCESSIVE SAMPLING

This work is designed to assess the effect of non-response in estimation of the current population mean in two-phase successive sampling on two occasions. Sub-sampling technique of non-respondents has been used and exponential methods of estimation under two-phase successive sampling arrangement have been proposed. Properties of the proposed estimation procedures have been examined. Empirical studies are carried out to justify the suggested estimation procedures and suitable recommendations

G. N. Singh, M. Khetan, S. Maurya

Statistics in Transition New Series, Volume 17 , ISSUE 2, 163–182

Research paper | 01-November-2017

SAE TEACHING USING SIMULATIONS

The increasing interest in applying small area estimation methods urges the needs for training in small area estimation. To better understand the behaviour of small area estimators in practice, simulations are a feasible way for evaluating and teaching properties of the estimators of interest. By designing such simulation studies, students gain a deeper understanding of small area estimation methods. Thus, we encourage to use appropriate simulations as an additional interactive tool in teaching

Jan Pablo Burgard, Ralf Münnich

Statistics in Transition New Series, Volume 16 , ISSUE 4, 603–610

Article | 07-July-2017

M-ESTIMATORS IN BUSINESS STATISTICS

Recent years have seen a dynamic development in statistical methods for analysing data contaminated with outliers. One of the more important techniques that can deal with outlying observations is robust regression, which represents four decades of research. Until recently the implementation of robust regression methods, such as M-estimation or MM-estimation, was limited owing to their iterative nature. With advances in computing power and the growing availability of statistical packages, such

Grażyna Dehnel

Statistics in Transition New Series, Volume 17 , ISSUE 4, 749–762

Research paper | 01-November-2017

SAE EDUCATION CHALLENGES TO ACADEMICS AND NSI

The aim of the paper is to present some experiences in teaching Small Area Estimation (SAE). SAE education experiences and challenges are analysed from the academic side and from the NSI side. An attempt was undertaken to discuss SAE issues in a wider perspective of teaching statistics. In particular, the topics refer to Polish conditions, but they are presented against the background of selected international experiences and practices. Information comes from a special inquiry - a survey

Elżbieta Gołata

Statistics in Transition New Series, Volume 16 , ISSUE 4, 611–630

Research Article | 03-March-2021

On the generalisation of Quatember's bootstrap

The problem of the estimation of the design-variance and the design-MSE of different estimators and predictors is considered. Bootstrap algorithms applicable to complex sampling designs are used. A generalisation of the bootstrap procedure studied by Quatember (2014) is proposed. In most of the cases considered in our simulation study it leads to more accurate estimates (or to very similar ones in remaining cases) of the designMSE and the design-variance compared with the original algorithm and

Tomasz Żądło

Statistics in Transition New Series, Volume 22 , ISSUE 1, 163–178

Article | 06-July-2017

A COMPARISON OF SMALL AREA ESTIMATION METHODS FOR POVERTY MAPPING

We review main small area estimation methods for the estimation of general nonlinear parameters focusing on FGT family of poverty indicators introduced by Foster, Greer and Thorbecke (1984). In particular, we consider direct estimation, the Fay-Herriot area level model (Fay and Herriot, 1979), the method of Elbers, Lanjouw and Lanjouw (2003) used by the World Bank, the empirical Best/Bayes (EB) method of Molina and Rao (2010) and its extension, the Census EB, and finally the hierarchical Bayes

María Guadarrama, Isabel Molina, J. N. K. Rao

Statistics in Transition New Series, Volume 17 , ISSUE 1, 41–66

Article | 06-July-2017

KERNEL ESTIMATION OF CUMULATIVE DISTRIBUTION FUNCTION OF A RANDOM VARIABLE WITH BOUNDED SUPPORT

In the paper methods of reducing the so-called boundary effects, which appear in the estimation of certain functional characteristics of a random variable with bounded support, are discussed. The methods of the cumulative distribution function estimation, in particular the kernel method, as well as the phenomenon of increased bias estimation in boundary region are presented. Using simulation methods, the properties of the modified kernel estimator of the distribution function are investigated

Aleksandra Baszczyńska

Statistics in Transition New Series, Volume 17 , ISSUE 3, 541–556

Sampling Methods | 12-July-2018

INTERACTION BETWEEN DATA COLLECTION AND ESTIMATION PHASES IN SURVEYS WITH NONRESPONSE

Inference in surveys with nonresponse has been studied extensively in the literature with a focus on the estimation phase. Propensity weighting and calibrated weighting are among the adjustment methods used to reduce the nonresponse bias. The data collection phase has come into focus more recently; the literature on adaptive survey design emphasizes representativeness and degree of balance as desirable properties of the response obtained from a probability sample. We take an integrated view

Carl-Erik Särndal, Imbi Traat, Kaur Lumiste

Statistics in Transition New Series, Volume 19 , ISSUE 2, 183–200

Article | 05-September-2021

A new reciprocal Rayleigh extension: properties, copulas, different methods of estimation and a modified right-censored test for validation

In this article, a new reciprocal Rayleigh extension called the Xgamma reciprocal Rayleigh model is defined and studied. The relevant statistical properties are derived, and the useful results related to the convexity and concavity are addressed. We discussed the estimation of the parameters using different estimation methods such as the maximum likelihood estimation method, the ordinary least squares estimation method, the weighted least squares estimation method, the Cramer-Von-Mises

Haitham M. Yousof, M. Masoom Ali, Hafida Goual, Mohamed Ibrahim

Statistics in Transition New Series, Volume 22 , ISSUE 3, 99–121

Research paper | 01-November-2017

OPERATIONALIZATION AND ESTIMATION OF BALANCED DEVELOPMENT INDEX FOR POLAND 1999-2016

Stemming from assumption that Gross Domestic Product is an index oversimplifying economic development and not reflecting socio-economic development, the paper presents conceptualization, operationalization and estimation of Balanced Development Index (BDI), concerning both economic and social development in Poland. Actual values of this index as well as its four composite components (middle-level indexes) are presented for 1999-2013. A statistical model allowing estimation of BDI values as well

Andrzej K. Koźmiński, Adam Noga, Katarzyna Piotrowska, Krzysztof Zagórski

Statistics in Transition New Series, Volume 16 , ISSUE 3, 461–487

Article | 06-July-2017

ESTIMATION OF MEAN ON THE BASIS OF CONDITIONAL SIMPLE RANDOM SAMPLE

Estimation of the population mean in a finite and fixed population on the basis of the conditional simple random sampling design dependent on order statistics (quantiles) of an auxiliary variable is considered. Properties of the well-known Horvitz-Thompson and ratio type estimators as well as the sample mean are taken into account under the conditional simple random sampling designs. The considered examples of empirical analysis lead to the conclusion that under some additional conditions the

Janusz Wywiał

Statistics in Transition New Series, Volume 17 , ISSUE 3, 411–428

Article | 15-September-2020

Small area estimation: its evolution in five decades

The paper is an attempt to trace some of the early developments of small area estimation. The basic papers such as the ones by Fay and Herriott (1979) and Battese, Harter and Fuller (1988) and their follow-ups are discussed in some details. Some of the current topics are also discussed.

Malay Ghosh

Statistics in Transition New Series, Volume 21 , ISSUE 4, 1–22

Article | 01-December-2012

Probabilistic Joint State Estimation of Robot and Non-static Objects for Mobile Manipulation

In this paper, a unified and probabilistic method is proposed for simultaneously localization of a mobile service robot and states estimation of surrounding objects and co-existing people. This method allows intelligent robots to navigate reliably in dynamic environments and provide home-care services based on joint localization results. The algorithm makes use of probabilistic model to represent non-static people and objects states. Moreover, Rao-Blackwellized particle filters (RBPFs) are

Kun Qian, Xudong Ma, Xian Zhong Dai, Fang Fang, Bo Zhou

International Journal on Smart Sensing and Intelligent Systems, Volume 5 , ISSUE 4, 1081–1096

Article | 24-July-2017

Sampling Error in Relation to Cyst Nematode Population Density Estimation in Small Field Plots

Cyst nematodes are serious plant-parasitic pests which could cause severe yield losses and extensive damage. Since there is still very little information about error of population density estimation in small field plots, this study contributes to the broad issue of population density assessment. It was shown that there was no significant difference between cyst counts of five or seven bulk samples taken per each 1-m2 plot, if average cyst count per examined plot exceeds 75 cysts per 100 g of

VESNA ZUPUNSKI, RADIVOJE JEVTIC, VESNA SPASIC JOKIC, LJUBICA ZUPUNSKI, MIRJANA LALOSEVIC, MIHAJLO CIRIC, ZIVKO CURCIC

Journal of Nematology, Volume 49 , ISSUE 2, 150–155

Article | 20-December-2020

A new generalization of the Pareto distribution and its applications

This paper introduces a new generalization of the Pareto distribution using the MarshallOlkin generator and the method of alpha power transformation. This new model has several desirable properties appropriate for modelling right skewed data. The Authors demonstrate how the hazard rate function and moments are obtained. Moreover, an estimation for the new model parameters is provided, through the application of the maximum likelihood and maximum product spacings methods, as well as the Bayesian

Ehab M. Almetwally, Hanan A. Haj Ahmad

Statistics in Transition New Series, Volume 21 , ISSUE 5, 61–84

Research paper | 30-October-2017

JOINT CALIBRATION ESTIMATOR FOR DUAL FRAME SURVEYS

estimation variable and the auxiliary variables employed in the calibration. The JCE achieves better performance when the auxiliary variables can fully explain the variability in the study variables or at least when the auxiliary variables are strong correlates of the estimation variables. As opposed to the standard dual frame estimators, the JCE does not require domain membership information. Even if included in the JCE auxiliary variables, the effect of the randomly misclassified domains does not

Mahmoud A. Elkasabi, Steven G. Heeringa, James M. Lepkowski

Statistics in Transition New Series, Volume 16 , ISSUE 1, 7–36

Sampling Methods | 22-July-2018

MODIFIED RECURSIVE BAYESIAN ALGORITHM FOR ESTIMATING TIME-VARYING PARAMETERS IN DYNAMIC LINEAR MODELS

Estimation in Dynamic Linear Models (DLMs) with Fixed Parameters (FPs) has been faced with considerable limitations due to its inability to capture the dynamics of most time-varying phenomena in econometric studies. An attempt to address this limitation resulted in the use of Recursive Bayesian Algorithms (RBAs) which is also affected by increased computational problems in estimating the Evolution Variance (EV) of the time-varying parameters. In this paper, we propose a modified RBA for

O. Olawale Awe, A. Adedayo Adepoju

Statistics in Transition New Series, Volume 19 , ISSUE 2, 239–258

Research Article | 01-September-2017

UNSUPERVISED LEARNING FOR RIPENESS ESTIMATION FROM GRAPE SEEDS IMAGES

Estimating the current stage of grape ripeness is a crucial step in wine making and becomes especially important during harvesting. Visual inspection of grape seeds is one method to achieve this goal without performing chemical analysis, however this method is prone to failure. In this paper, we propose an unsupervised visual inspection system for grape ripeness estimation using the Dirichlet Mixture Model (DMM). Experimental analysis using real world data demonstrates that our approach can be

S. Hernández, L. Morales, A. Urrutia

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 3, 594–612

Article | 28-August-2018

ESTIMATION OF THE SEASONAL DEMAND FOR COOLING BASED ON THE SHORT-TERM DATA

The paper analyzes the possibility of using the energy signature method based on the linear regression to determine the seasonal energy demand for cooling and ventilation in the office building. The “extended” energy signature method (H-m method) was described and applied. In accordance with Standard (EN 15603) the estimation of energy consumption for cooling can be performed for a period shorter than the entire season, but data range must be appropriate to obtain the correct accuracy of the

Dorota BARTOSZ, Aleksandra SPECJAŁ

Architecture, Civil Engineering, Environment, Volume 10 , ISSUE 2, 133–143

Article | 22-July-2019

STATISTICAL INFERENCE OF EXPONENTIAL RECORD DATA UNDER KULLBACK-LEIBLER DIVERGENCE MEASURE

Based on one parameter exponential record data, we conduct statistical inferences (maximum likelihood estimator and Bayesian estimator) for the suggested model parameter. Our second aim is to predict the future (unobserved) records and to construct their corresponding prediction intervals based on observed set of records. In the estimation and prediction processes, we consider the square error loss and the Kullback-Leibler loss functions. Numerical simulations were conducted to evaluate the

Raed r. . Abu Awwad

Statistics in Transition New Series, Volume 20 , ISSUE 2, 1–14

Research Communicate | 20-November-2017

SAMPLE ALLOCATION IN ESTIMATION OF PROPORTION IN A FINITE POPULATION DIVIDED AMONG TWO STRATA

Dominik Sieradzki, Wojciech Zieliński

Statistics in Transition New Series, Volume 18 , ISSUE 3, 541–548

Research Article | 15-February-2020

A Novel Approach To Improve Vehicle Speed Estimation Using Smartphone’s INS/GPS Sensors

is proposed which enhances the accuracy of speed estimation. It is envisaged that with increasing estimation accuracy, the application of multi-sensor fusion in autonomous vehicles will be greatly enhanced.

Arijit Chowdhury, Tapas Chakravarty, P. Balamuralidhar

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 5, 1–6

Research Article | 27-May-2018

A NEW AND UNIFIED APPROACH IN GENERALIZING THE LINDLEY’S DISTRIBUTION WITH APPLICATIONS

This paper proposes a new family of continuous distributions with one extra shape parameter called the generalized Zeghdoudi distributions (GZD). We investigate the shapes of the density and hazard rate function. We derive explicit expressions for some of its mathematical quantities. Various statistical properties like stochastic ordering, moment method, maximum likelihood estimation, entropies and limiting distribution of extreme order statistics are established. We prove the flexibility of

Lahsen Bouchahed, Halim Zeghdoudi

Statistics in Transition New Series, Volume 19 , ISSUE 1, 61–74

Research Article | 27-February-2017

IMPROVING THE METHODS OF ESTIMATION OF THE UNIT TRAIN EFFECTIVENESS

Dmytro KOZACHENKO, Roman VERNIGORA, Volodymyr BALANOV, Nazar SANNYTSKYY, Nikolay BEREZOVY, Tetiana BOLVANOVSKA

Transport Problems, Volume 11 , ISSUE 3, 91–101

Article | 24-August-2017

EFFICIENT FAMILY OF RATIO-TYPE ESTIMATORS FOR MEAN ESTIMATION IN SUCCESSIVE SAMPLING ON TWO OCCASIONS USING AUXILIARY INFORMATION

In this paper, we proposed an efficient family of ratio-type estimators using one auxiliary variable for the estimation of the current population mean under successive sampling scheme. This family of estimators have been studied by Ray and Sahai (1980) under simple random sampling using one auxiliary variable for estimation of the population mean. Using these estimators in successive sampling, the expression for bias and mean squared error of the proposed estimators are obtained up to the first

Nazeema T. Beevi, C. Chandran

Statistics in Transition New Series, Volume 18 , ISSUE 2, 227–245

Research Article | 13-June-2021

Small area estimates of the low work intensity indicator at voivodeship level in Poland

The EU Statistics on Income and Living Conditions (EU-SILC) has provided annual esti mates of the number of labour market indicators for EU countries since 2003, with an almost exclusive focus on national rates. However, it is impossible to obtain reliable direct estimates of labour market statistics at low levels based on the EU-SILC survey. In such cases, model based small area estimation can be used. In this paper, the low work intensity indicator for the spatial domains in Poland between

Łukasz Wawrowski, Maciej Beręsewicz

Statistics in Transition New Series, Volume 22 , ISSUE 2, 155–172

Article | 05-September-2021

A new count data model applied in the analysis of vaccine adverse events and insurance claims

The article presents a new probability distribution, created by compounding the Poisson distribution with the weighted exponential distribution. Important mathematical and statistical properties of the distribution have been derived and discussed. The paper describes the proposed model’s parameter estimation, performed by means of the maximum likelihood method. Finally, real data sets are analyzed to verify the suitability of the proposed distribution in modeling count data sets

Showkat Ahmad Dar, Anwar Hassan, Ahmad Para Bilal, Sameer Ahmad Wani

Statistics in Transition New Series, Volume 22 , ISSUE 3, 157–174

Article | 06-July-2017

A NEW MEDIAN BASED RATIO ESTIMATOR FOR ESTIMATION OF THE FINITE POPULATION MEAN

The present paper deals with a new median based ratio estimator for the estimation of finite population means in the absence of an auxiliary variable. The bias and mean squared error of the proposed median based ratio estimator are obtained. The performance of the median based ratio estimator is compared with that of the SRSWOR sample mean, ratio estimator and linear regression estimator for certain natural population. It is shown from the numerical comparisons that the proposed median based

J. Subramani

Statistics in Transition New Series, Volume 17 , ISSUE 4, 591–604

Research Article | 01-December-2017

EVALUATION OF BEHAVIOR ESTIMATION USING WARD'S METHOD IN MULTIFUNCTION OUTLET SYSTEM

appliances. The function uses Ward's method which is an unsupervised learning for estimation of a user's behavior. In this paper, we evaluated a result of estimate of a user's behavior from sensor data by Ward's method.

Sho Kimura, Toshihiko Sasama, Takao Kawamura, Kazunori Sugahara

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 4, 920–934

Article | 01-September-2015

Classification of artificial light sources and estimation of Color Rendering Index using RGB sensors, K Nearest Neighbor and Radial Basis Function

light sources and to select an estimation model of the CRI and the CCT using a low cost RGB sensor. The model estimation has been developed in this work and a separated algorithm for each source type has been built. The results show that using a K-Nearest Neighbor classifier, the error resulted less than $3.6%$. The error of the model estimation for the LED was 1.8%, for fluorescent light sources 0.09% and 1.2% for incandescent light sources.

J.-S. Botero V., F.-E. López G., J.-F. Vargas B.

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 3, 1505–1524

Research paper | 01-November-2017

SMALL AREA ESTIMATION FOR SKEWED DATA IN THE PRESENCE OF ZEROES

Forough Karlberg

Statistics in Transition New Series, Volume 16 , ISSUE 4, 541–562

Article | 01-June-2016

NON INVASIVE ESTIMATION OF BLOOD UREA CONCENTRATION USING NEAR INFRARED SPECTROSCOPY

This paper details about the noninvasive estimation of Urea concentration in blood using near infrared spectroscopy (NIRS) and Artificial neural network based prediction model. The absorption spectrum of the urea has been studied experimentally in order to choose the wavelengths of peak absorption. For this purpose, IR absorption spectrum of 0.1M aqueous urea solution has been collected and analyzed in second overtone region of the near-infra red spectra using the Bruker tensor 27 FTIR

Swathi Ramasahayam, Shubhajit Roy Chowdhury

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 2, 449–467

Article | 03-July-2017

THE APPLICATION OF BŰHLMANN-STRAUB MODEL TO THE ESTIMATION OF NET PREMIUM RATES DEPENDING ON THE AGE OF THE INSURED IN THE MOTOR THIRD LIABILITY INSURANCE

One of the basic variables used in the process of tariff calculation of premiums in motor liability insurance is the age of the insured. In this type of insurance offered by insurers operating on the Polish market, this variable is taken into account in the ratemaking by discounts and increases in assigned premium, known as the net premiums rates. The aim of this work is to propose a method of rate estimation of net premiums in the groups of the motor third liability insurance portfolio of

Anna Szymańska

Statistics in Transition New Series, Volume 18 , ISSUE 1, 151–165

Article | 01-June-2016

EXPERIMENTAL AND THEORETICAL VALIDATION METHOD FOR ESTIMATION OF STRAIGHTNESS DEVIATION AND ASSOCIATED UNCERTAINTY IN CNC-CMM MEASUREMENT

Salah H.R. Ali, M.A.H. Khalafalla, Ihab H. Naeim, Sarwat Z.A. Zahwi

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 2, 397–418

Article | 15-March-2019

EXTENDED EXPONENTIATED POWER LINDLEY DISTRIBUTION

In this study, we introduce a new model called the Extended Exponentiated Power Lindley distribution which extends the Lindley distribution and has increasing, bathtub and upside down shapes for the hazard rate function. It also includes the power Lindley distribution as a special case. Several statistical properties of the distribution are explored, such as the density, hazard rate, survival, quantile functions, and moments. Estimation using the maximum likelihood method and inference on a

V. Ranjbar, M. Alizadeh, G. G. Hademani

Statistics in Transition New Series, Volume 19 , ISSUE 4, 621–643

Article | 05-September-2021

Bayesian estimation and prediction based on Rayleigh record data with applications

Raed R. Abu Awwad, Omar M. Bdair, Ghassan K. Abufoudeh

Statistics in Transition New Series, Volume 22 , ISSUE 3, 59–79

Article | 20-September-2020

Generalised Odd Frechet Family of Distributions: Properties and Applications

A new distribution called Generalized Odd Fréchet (GOF) distribution is presented and its properties explored. Some structural properties of the proposed distribution, including the shapes of the hazard rate function, moments, conditional moments, moment generating function, skewness, and kurtosis are presented. Mean deviations, Lorenz and Bonferroni curves, Rényi entropy, and the distribution of order statistics are given. The maximum likelihood estimation technique is used to

Shahdie Marganpoor, Vahid Ranjbar, Morad Alizadeh, Kamel Abdollahnezhad

Statistics in Transition New Series, Volume 21 , ISSUE 3, 109–128

Article | 01-April-2018

Estimation Algorithm for Low Frequency Seismic Motions Based on Extended Semblance Function

seismograms are calculated through the fast algorithm, and the multi-path parameters as well as the difference of travel time between a reference position and the seismographic stations are given by an optimization algorithm in the frequency domain. The new approach can work under conditions of refraction interference, and improve the estimation performance by using an extended semblance function. Its effectiveness is demonstrated through some numerical examples, and it is shown that the proposed

Lianming Sun

International Journal of Advanced Network, Monitoring and Controls, Volume 1 , ISSUE 1, –

Article | 01-June-2015

RESEARCH ON CAMERA-BASED HUMAN BODY TRACKING USING IMPROVED CAM-SHIFT ALGORITHM

can be detected. Then, with the analysis of particle filtering and traditional Cam-shift algorithm, we introduce a new human body tracking method that is able to choose the target automatically due to the detection result. On the basis of the detection and tracking results, the algorithm of motion parameter estimation is analyzed. Finally, a set of human body detection and tracking experiments are designed to demonstrate the effectiveness of the proposed algorithms.

Jiude Li

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 2, 1104–1122

Research Article | 27-May-2018

POWER ISHITA DISTRIBUTION AND ITS APPLICATION TO MODEL LIFETIME DATA

A study on two-parameter power Ishita distribution (PID), of which Ishita distribution introduced by Shanker and Shukla (2017 a) is a special case, has been carried out and its important statistical properties including shapes of the density, moments, skewness and kurtosis measures, hazard rate function, and stochastic ordering have been discussed. The maximum likelihood estimation has been discussed for estimating its parameters. An application of the distribution has been explained with a

Kamlesh Kumar Shukla, Rama Shanker

Statistics in Transition New Series, Volume 19 , ISSUE 1, 135–148

Research paper | 01-November-2017

COVARIATE SELECTION FOR SMALL AREA ESTIMATION IN REPEATED SAMPLE SURVEYS

If the implementation of small area estimation methods to multiple editions of a repeated sample survey is considered, then the question arises which covariates to use in the models. Applying standard model selection procedures independently to the different editions of the survey may identify different sets of covariates for each edition. If the small area predictions are sensitive to the different models, this is undesirable in official statistics since monitoring change over time of

Jan A. van den Brakel, Bart Buelens

Statistics in Transition New Series, Volume 16 , ISSUE 4, 523–540

Research Article | 27-December-2017

EVALUATION OF DIFFERENT SENSING APPROACHES CONCERNING TO NONDESTRUCTIVE ESTIMATION OF LEAF AREA INDEX (LAI) FOR WINTER WHEAT

Different approaches of non-destructive estimation of the LAI in winter wheat were compared. Plant height had weak relation with the LAI, while estimated biomass showed high logarithmic relationship (R2=0.839). NDRE and REIP were logarithmically well related to the LAI (R2=0.726 and 0.779 respectively). Saturation effect of NDRE and REIP was less than NDVI. Some RGB-based indices also showed good potential to estimate the LAI. Among the indices, Gm, GMB, RMB, and NRMB were better related to the

H. Tavakoli, S.S. Mohtasebi, R. Alimardani, R. Gebbers

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 1, 337–359

Article | 01-June-2016

A MACHINE VISION SYSTEM FOR ESTIMATION OF THEAFLAVINS AND THEARUBIGINS IN ORTHODOX BLACK TEA

Orthodox black tea quality depends upon the amount of certain organic compounds present and out of these, theaflavins (TF) and thearubigins (TR) are the most important ones While TF is responsible for attractive golden colour, increased brightness and astringency in tea liquor, TR is reddish brown, reduces the brightness of tea liquor and contribute mostly for the ashy taste of the liquor with minor improvement in astringency. The rapid estimation of TF and TR thus may resolve the problem of

Amitava Akuli, Abhra Pal, Gopinath Bej, Tamal Dey, Arunangshu Ghosh, Bipan Tudu, Nabarun Bhattacharyya, Rajib Bandyopadhyay

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 2, 709–731

Article | 01-December-2016

RANGE IMAGE SENSOR BASED EYE GAZE ESTIMATION BY USING THE RELATIONSHIP BETWEEN THE FACE AND EYE DIRECTIONS

In this paper, we estimate the eye gaze by using the face direction to estimate the object of interest in an extensive area such as an educational display or museum exhibit. However, the direction of the gaze may differ from that of the face. Therefore, our approach was to use a method that utilizes both the face and eye directions to improve the accuracy of our estimation compared to only using the face direction. The first part of our study involved apprehending the relationship between the

Haruya Tamaki, Tsugunosuke Sakai, Yosuke Ota, Fusako Kusunoki, Shigenori Inagaki, Ryohei Egusa, Masanori Sugimoto, Hiroshi Mizoguchi

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 4, –

Article | 05-June-2013

FIELD PROGRAMMABLE GATE ARRAY BASED EMBEDDED SYSTEM FOR NON-INVASIVE ESTIMATION OF HEMOGLOBIN IN BLOOD USING PHOTOPLETHYSMOGRAPHY

Chetan Sharma, Sachin Kumar, Anshul Bhargava, Shubhajit Roy Chowdhury

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 3, 1267–1282

Article | 15-March-2019

DEVELOPMENT OF CHAIN-TYPE EXPONENTIAL ESTIMATORS FOR POPULATION VARIANCE IN TWOPHASE SAMPLING DESIGN IN PRESENCE OF RANDOM NON-RESPONS

In this paper, an investigation has been carried out to deal with a unified approach of estimation procedures of population variance in two-phase sampling design under missing at random non-response mechanism circumstances. Using two auxiliary variables, we have developed different chain-type exponential estimators of finite population variance for two different set-ups and studied their properties under the different assumption of random non-response considered by Tracy and Osahan (1994). The

G. N. Singh, Amod Kumar, Gajendra K. Vishwakarma

Statistics in Transition New Series, Volume 19 , ISSUE 4, 575–596

Research Article | 18-March-2020

Change-point detection in CO2 emission-energy consumption nexus using a recursive Bayesian estimation approach

This article focuses on the synthesis of conditional dependence structure of recursive Bayesian estimation of dynamic state space models with time-varying parameters using a newly modified recursive Bayesian algorithm. The results of empirical applications to climate data from Nigeria reveals that the relationship between energy consumption and carbon dioxide emission in Nigeria reached the lowest peak in the late 1980s and the highest peak in early 2000. For South Africa, the slope trajectory

Olushina Olawale Awe, Abosede Adedayo Adepoju

Statistics in Transition New Series, Volume 21 , ISSUE 1, 123–136

Research Article | 13-June-2021

Interviewer allocation through interview–reinterview nested design for response error estimation in sample surveys

In surveys, non-sampling errors, due to their complex nature, are more challenging to quantify compared to sampling errors. Avoiding the release of these errors, however, results in biased survey estimates. In our previous paper, we devised the best interviewer allocation technique by using a nested experimental design to study response error estimation. In this study, in order to illustrate the effectiveness of this methodology in a different context, we apply it in interview-reinterview

Fidan Mahmut Fahmi, H. Öztaş Ayhan, Ìnci Batmaz

Statistics in Transition New Series, Volume 22 , ISSUE 2, 67–93

Research paper | 31-October-2017

POLICY-ORIENTED INFERENCE AND THE ANALYST-CLIENT COOPERATION. AN EXAMPLE FROM SMALL-AREA STATISTICS

We show on an application to small-area statistics that efficient estimation is not always conducive to good policy decisions because the established inferential procedures have no capacity to incorporate the priorities and preferences of the policy makers and the related consequences of incorrect decisions. A method that addresses these deficiencies is described. We argue that elicitation of the perspectives of the client (sponsor) and their quantification are essential elements of the

Nicholas T. Longford

Statistics in Transition New Series, Volume 16 , ISSUE 1, 65–82

Research paper | 01-November-2017

BORROWING INFORMATION OVER TIME IN BINOMIAL/LOGIT NORMAL MODELS FOR SMALL AREA ESTIMATION

Linear area level models for small area estimation, such as the Fay-Herriot model, face challenges when applied to discrete survey data. Such data commonly arise as direct survey estimates of the number of persons possessing some characteristic, such as the number of persons in poverty. For such applications, we examine a binomial/logit normal (BLN) model that assumes a binomial distribution for rescaled survey estimates and a normal distribution with a linear regression mean function for

Carolina Franco, William R. Bell

Statistics in Transition New Series, Volume 16 , ISSUE 4, 563–584

Article | 06-July-2017

VARIATIONAL APPROXIMATIONS FOR SELECTING HIERARCHICAL MODELS OF CIRCULAR DATA IN A SMALL AREA ESTIMATION APPLICATION

, within spatio temporal domains subdivided by the mode of fishing. Because many of these domains have small sample sizes, small area estimation methods are developed. Bayesian inference for the circular distributions on the 24-hour clock is conducted, based on a large set of observed daily departure times from another National Marine Fisheries Service study, the Coastal Household Telephone Survey. A novel variational/Laplace approximation to the posterior distribution allows fast comparison of a large

Daniel Hernandez-Stumpfhauser, F. Jay Breidt, Jean D. Opsomer

Statistics in Transition New Series, Volume 17 , ISSUE 1, 91–104

Article | 06-July-2017

SUJATHA DISTRIBUTION AND ITS APPLICATIONS

, stochastic ordering, mean deviations, Bonferroni and Lorenz curves, and stress-strength reliability have been discussed. Estimation of its parameter has been discussed using the method of maximum likelihood and the method of moments. The applications and goodness of fit of the distribution have been discussed with three real lifetime data sets and the fit has been compared with one-parameter lifetime distributions including Akash, Shanker, Lindley and exponential distributions.

Rama Shanker

Statistics in Transition New Series, Volume 17 , ISSUE 3, 391–410

Research Article | 24-August-2017

A THREE-PARAMETER WEIGHTED LINDLEY DISTRIBUTION AND ITS APPLICATIONS TO MODEL SURVIVAL TIME

of dispersion have been derived and discussed. The reliability properties, including hazard rate function and mean residual life function, have been discussed. The estimation of its parameters has been discussed using the maximum likelihood method and the applications of the distribution have been explained through some survival time data of a group of patients suffering from head and neck cancer, and the fit has been compared with a one-parameter Lindley distribution and a two-parameter weighted

Rama Shanker, Kamlesh Kumar Shukla, Amarendra Mishra

Statistics in Transition New Series, Volume 18 , ISSUE 2, 291–310

Article | 27-May-2019

ON THE SMOOTHED PARAMETRIC ESTIMATION OF MIXING PROPORTION UNDER FIXED DESIGN REGRESSION MODEL

Y. S. Ramakrishnaiah, Manish Trivedi, Konda Satish

Statistics in Transition New Series, Volume 20 , ISSUE 1, 87–102

Article | 20-September-2020

Power Size Biased Two-Parameter Akash Distribution

In this paper, the two-parameter Akash distribution is generalized to size-biased twoparameter Akash distribution (SBTPAD). A further modification to SBTPAD is introduced, creating the power size-biased two-parameter Akash distribution (PSBTPAD). Several statistical properties of PSBTPAD distribution are proved. These properties include the following: moments, coefficient of variation, coefficient of skewness, coefficient of kurtosis, the maximum likelihood estimation of the distribution

Khaldoon Alhyasat, Ibrahim Kamarulzaman, Amer Ibrahim Al-Omari, Mohd Aftar Abu Bakar

Statistics in Transition New Series, Volume 21 , ISSUE 3, 73–91

Article | 09-April-2018

Development of Levenberg-Marquardt Method Based Iteration Square Root Cubature Kalman Filter ant its applications

Levenberg-Marquardt(abbr. L-M) method based iterative square root cubature Kalman filter (ISRCKFLM) is proposed to improve the low state estimation accuracy of nonlinear state estimation due to large initial estimation error and nonlinearity of measurement equation. The measurement update of square root cubature Kalman filter (SRCKF) is transformed to the problem of nonlinear least square error, then we use L-M method to solve it and obtain the optimal state estimation and covariance, so the

Jing Mu, Changyuan Wang

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 2, 98–106

Article | 01-September-2015

THE USE OF ARTIFICIAL NEURAL NETWORKS IN THE ESTIMATION OF THE PERCEPTION OF SOUND BY THE HUMAN AUDITORY SYSTEM

their suitability over other modeling methods for the task of perception modeling, taking into account development and implementation complexity. It will be shown that while known points on the perception scales of loudness and pitch can be used to objectively test the suitability of artificial neural networks, it is in the estimation of the perception of sound from the unknown (or unseen) data points that this method excels.

D. Riordan, P. Doody, J. Walsh

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 3, 1806–1836

Article | 07-May-2018

Levenberg-Marquardt Method Based Iterative Square Root Cubature Kalman Filter and its Applications to Maneuvering Re-entry Target Tracking

Levenberg-Marquardt (abbr.L-M) method based iterative square root cubature Kalman filter (abbr. ISRCKFLM) inherits the numerical stability of square root Cubature Kalman filter and effectively suppresses the influence of the larger initial estimation error and the nonlinearity of the measurement equation on the state estimation in the nonlinear state estimation due to obtaining the optimal state and variance estimates using the latest measurement through L-M method. We apply the ISRCKFLM

Mu Jing, Wang Changyuan

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 2, 10–13

Research paper | 31-October-2017

ROBUST REGRESSION IN MONTHLY BUSINESS SURVEY

There are many sample surveys of populations that contain outliers (extreme values). This is especially true in business, agricultural, household and medicine surveys. Outliers can have a large distorting influence on classical statistical methods that are optimal under the assumption of normality or linearity. As a result, the presence of extreme observations may adversely affect estimation, especially when it is carried out at a low level of aggregation. To deal with this problem, several

Grażyna Dehnel

Statistics in Transition New Series, Volume 16 , ISSUE 1, 137–152

Research Article | 01-December-2017

LOAD AWARE CHANNEL ESTIMATION AND CHANNEL SCHEDULING FOR 2.4GHZ FREQUENCY BAND BASED WIRELESS NETWORKS FOR SMART GRID APPLICATIONS

efficient data communication. During this scheme, if node attains a channel it must wait for a network reconfiguration time for moving to next channel. Hence, during this time other nodes are allowed for moving to the new channel. Secondly, for moving to the new channel load aware channel estimation is proposed to assess the possibility of traffic weight assignment at each channel. Finally, the Particle swarm optimization (PSO) based collision avoiding multiple-channel based superframe scheduling is

Vikram K, Sarat Kumar Sahoo

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 4, 879–902

Research Article | 13-December-2018

DEALING WITH HETEROSKEDASTICITY WITHIN  THE MODELING OF THE QUALITY OF LIFE  OF OLDER PEOPLE

Using the estimation method of ordinary least squares leads to unreliable results in the case of heteroskedastic linear regression model. Other estimation methods are described, including weighted least squares, division of the sample and heteroskedasticity-consistent covariance matrix estimators, all of which can give estimators with better properties than ordinary least squares. The methods are presented giving the example of modelling quality of life of older people, based on a data set from

Katarzyna Jabłońska

Statistics in Transition New Series, Volume 19 , ISSUE 3, 423–452

Article | 06-July-2017

TRANSMUTED KUMARASWAMY DISTRIBUTION

Muhammad Shuaib Khan, Robert King, Irene Lena Hudson

Statistics in Transition New Series, Volume 17 , ISSUE 2, 183–210

Article | 24-August-2017

SEQUENTIAL DATA WEIGHTING PROCEDURES FOR COMBINED RATIO ESTIMATORS IN COMPLEX SAMPLE SURVEYS

important reasons are weighting for unequal probability of selection, compensation for nonresponse, and post-stratification. Many highly efficient estimation methods in survey sampling require strong information about auxiliary variables, x. The most common estimation methods using auxiliary information in estimation stage are regression and ratio estimator. This paper proposes a sequential data weighting procedure for the estimators of combined ratio mean in complex sample surveys and general variance

Aylin Alkaya, H. Öztaş Ayhan, Alptekin Esin

Statistics in Transition New Series, Volume 18 , ISSUE 2, 247–270

Research Article | 13-December-2017

INVESTIGATION OF ADVANCED DATA PROCESSING TECHNIQUE IN MAGNETIC ANOMALY DETECTION SYSTEMS

Advanced methods of data processing in magnetic anomaly detection (MAD) systems are investigated. Raw signals of MAD based on component magnetic sensors are transformed into energy signals in the space of specially constructed orthonormalized functions. This procedure provides a considerable improvement of the SNR thus enabling reliable target detection. Estimation of the target parameters is implemented with the help of Genetic Algorithm. Numerous computer simulations show good algorithm

B. Ginzburg, L. Frumkis, B.Z. Kaplan, A. Sheinker, N. Salomonski

International Journal on Smart Sensing and Intelligent Systems, Volume 1 , ISSUE 1, 110–122

Article | 22-January-2018

A NEW ESTIMATOR OF MEAN USING DOUBLE SAMPLING

In this paper, we consider the problem of estimation of population mean of a study variable by making use of first-phase sample mean and first-phase sample median of the auxiliary variable at the estimation stage. The proposed new estimator of the population mean is compared to the sample mean estimator, ratio estimator and the difference type estimator for the fixed cost of the survey by using the concept of two-phase sampling. The magnitude of the relative efficiency of the proposed new

Kalyan Rao Vadlamudi, Stephen A. Sedory, Sarjinder Singh

Statistics in Transition New Series, Volume 18 , ISSUE 4, 637–650

Article | 20-September-2020

Poisson Weighted Ishita Distribution: Model for Analysis of Over-Dispersed Medical Count Data

A new over-dispersed discrete probability model is introduced, by compounding the Poisson distribution with the weighted Ishita distribution. The statistical properties of the newly introduced distribution have been derived and discussed. Parameter estimation has been done with the application of the maximum likelihood method of estimation, followed by the Monte Carlo simulation procedure to examine the suitability of the ML estimators. In order to verify the applicability of the proposed

Bilal Ahmad Para, Tariq Rashid Jan

Statistics in Transition New Series, Volume 21 , ISSUE 3, 171–184

Article | 01-June-2020

Application of iterated filtering to stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck process

Barndorff-Nielsen and Shephard (2001) proposed a class of stochastic volatility models in which the volatility follows the Ornstein–Uhlenbeck process driven by a positive Levy process without the Gaussian component. The parameter estimation of these models is challenging because the likelihood function is not available in a closed-form expression. A large number of estimation techniques have been proposed, mainly based on Bayesian inference. The main aim of the paper is to present an

Piotr Szczepocki

Statistics in Transition New Series, Volume 21 , ISSUE 2, 173–187

Article | 06-July-2017

SMALL AREA PREDICTION UNDER ALTERNATIVE MODEL SPECIFICATIONS

Construction of small area predictors and estimation of the prediction mean squared error, given different types of auxiliary information are illustrated for a unit level model. Of interest are situations where the mean and variance of an auxiliary variable are subject to estimation error. Fixed and random specifications for the auxiliary variables are considered. The efficiency gains associated with the random specification for the auxiliary variable measured with error are demonstrated. A

Andreea L. Erciulescu, Wayne A. Fuller

Statistics in Transition New Series, Volume 17 , ISSUE 1, 9–24

Article | 27-May-2019

MODELLING SENSITIVE ISSUES ON SUCCESSIVE WAVES

This paper addresses the problem of estimation of population mean of sensitive character using non-sensitive auxiliary variable at current wave in two wave successive sampling. A general class of estimator is proposed and studied under randomized and scrambled response model. Many existing estimators have been modified to work for sensitive population mean estimation. The modified estimators became the members of proposed general class of estimators. The detail properties of all the estimators

Kumari Priyanka, Pidugu Trisandhya

Statistics in Transition New Series, Volume 20 , ISSUE 1, 41–65

Article | 03-November-2017

APPLICATION OF SELF-TUNING FUZZY PID CONTROLLER ON INDUSTRIAL HYDRAULIC ACTUATOR USING SYSTEM IDENTIFICATION APPROACH

In this paper, Self Tuning Fuzzy PID controller is developed to improve the performance of the electro-hydraulic actuator. The controller is designed based on the mathematical model of the system which is estimated by using System Identification technique. The model is performed in linear discrete model to obtain a discrete transfer function for the system. Model estimation procedures are done by using System Identification Toolbox in Matlab. Data for model estimation is taken from an

Zulfatman, M. F. Rahmat

International Journal on Smart Sensing and Intelligent Systems, Volume 2 , ISSUE 2, 246–261

Article | 13-June-2021

A comparative study of a class of direct estimators for domain mean with a direct ratio estimator for domain mean using auxiliary character

Estimation techniques for a domain parameter play a very significant role in the theory of sample surveys. In the recent years many advanced methodologies have been developed for domain estimation. In particular, direct and synthetic estimators are applied for the estimation of domain mean in the government and private sectors under certain assumptions as to the size of the samples relating to particular domains. The findings demonstrate that the direct estimator fails to perform more

Brij Behari Khare, Ashutosh Ashutosh, Piyush Kant Rai

Statistics in Transition New Series, Volume 22 , ISSUE 2, 189–200

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