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  • Statistics In Transition

 

Research Article | 22-January-2018

RELATIONS FOR MOMENTS OF PROGRESSIVELY TYPE-II RIGHT CENSORED ORDER STATISTICS FROM ERLANG-TRUNCATED EXPONENTIAL DISTRIBUTION

In this paper, we establish some new recurrence relations for the single and product moments of progressively Type-II right censored order statistics from the Erlangtruncated exponential distribution. These relations generalize those established by Aggarwala and Balakrishnan (1996) for standard exponential distribution. These recurrence relations enable computation of mean, variances and covariances of all progressively Type-II right censored order statistics for all sample sizes in a simple

Mansoor Rashid Malik, Devendra Kumar

Statistics in Transition New Series, Volume 18 , ISSUE 4, 651–668

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

Research Article | 27-May-2018

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

Lahsen Bouchahed, Halim Zeghdoudi

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

Article | 20-September-2020

A New Quasi Sujatha Distribution

The aim of this paper is to introduce a new quasi Sujatha distribution (NQSD), of which the following are particular cases: the Sujatha distribution devised by Shanker (2016 a), the sizebiased Lindley distribution, and the exponential distribution. Its moments and momentsbased measures are derived and discussed. Statistical properties, including the hazard rate and mean residual life functions, stochastic ordering, mean deviations, Bonferroni and Lorenz curves and stress-strength reliability

Rama Shanker, Kamlesh Kumar Shukla

Statistics in Transition New Series, Volume 21 , ISSUE 3, 53–71

Research Article | 24-August-2017

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

In this paper a three-parameter weighted Lindley distribution, including Lindley distribution introduced by Lindley (1958), a two-parameter gamma distribution, a two-parameter weighted Lindley distribution introduced by Ghitany et al. (2011) and exponential distribution as special cases, has been suggested for modelling lifetime data from engineering and biomedical sciences. The structural properties of the distribution including moments, coefficient of variation, skewness, kurtosis and index

Rama Shanker, Kamlesh Kumar Shukla, Amarendra Mishra

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

Article | 22-July-2019

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

Raed r. . Abu Awwad

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

Article | 20-December-2020

The Gamma Kumaraswamy-G family of distributions: theory, inference and applications

In this paper, we introduce a new family of univariate continuous distributions called the Gamma Kumaraswamy-generated family of distributions. Most of its properties are studied in detail, including skewness, kurtosis, analytical comportments of the main functions, moments, stochastic ordering and order statistics. The next part of the paper focuses on a particular member of the family with four parameters, called the gamma Kumaraswamy exponential distribution. Among its advantages, the

Rana Muhammad Imran Arshad, Muhammad Hussain Tahir, Christophe Chesneau, Farrukh Jamal

Statistics in Transition New Series, Volume 21 , ISSUE 5, 17–40

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