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Sampling Methods | 20-November-2017

POPULATION VARIANCE ESTIMATION USING FACTOR TYPE IMPUTATION METHOD

RANJITA PANDEY, KALPANA YADAV

Statistics in Transition New Series, Volume 18 , ISSUE 3, 375–392

Research Article | 03-March-2021

On the generalisation of Quatember's bootstrap

Tomasz Żądło

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

Article | 13-December-2019

A NEW RATIO ESTIMATOR: AN ALTERNATIVE TO REGRESSION ESTIMATOR IN SURVEY SAMPLING USING AUXILIARY INFORMATION

The most dominant problem in the survey sampling is to obtain the better ratio estimators for the estimation of population mean or population variance. Estimation theory is enhanced by using the auxiliary information in order to improve on designs, precision and efficiency of estimators. A modified class of ratio estimator is suggested in this paper to estimate the population mean. Expressions for the bias and the mean square error of the proposed estimators are obtained. Both analytical and

Mir Subzar, S. Maqbool, T. A. Raja, Prayas Sharma

Statistics in Transition New Series, Volume 20 , ISSUE 4, 181–189

Article | 15-March-2019

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

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

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

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

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