Edgeworth expansion and the bootstrap for stratified sampling without replacement from a finite population

1993 ◽  
Vol 21 (4) ◽  
pp. 347-357 ◽  
Author(s):  
Jiahua Chen ◽  
R. R. Sitter
Keyword(s):  
Edgeworth Expansion ◽  
Finite Population ◽  
Stratified Sampling ◽  
Sampling Without Replacement

scholarly journals Bootstrap, jackknife and Edgeworth approximations for finite population L-statistics

2010 ◽  
Vol 51 ◽  
Author(s):  
Andrius Čiginas
Keyword(s):  
Distribution Function ◽  
Edgeworth Expansion ◽  
Finite Population ◽  
Normal Approximation ◽  
Bootstrap Approximation ◽  
True Distribution

In this paper we give exact bootstrap estimators for the parameters defining one-term Edgeworth expansion of distribution function of finite population L-statistic and compare these estimators with corresponding jackknife estimators. We also compare `````` true’ distribution of L-statistic with its normal approximation, Edgeworth expansion, empirical Edgeworth expansion and bootstrap approximation.

scholarly journals The Estimation of Finite Population Variance Under Stratified Sampling Technique

2021 ◽  
Author(s):  
Uzma Yasmeen ◽  
Muhammad Noor-ul-Amin
Keyword(s):  
Finite Population ◽  
Auxiliary Information ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Stratified Sampling ◽  
Auxiliary Variables ◽  
Population Variance ◽  
Variance Estimators ◽  
Usual Estimator ◽  
Study Population

The efficiency of the study variable can be improved by incorporating the information from the known auxiliary variables. Usually two techniques ratio and regression estimation are used with the help of auxiliary information in different approaches to acquire the high precision of the estimators. Considering the very heterogeneous population to get the size of the sample it may be originating impossible to get a sufficiently accurate and precise estimate by taking the simple random sampling technique from the complete population. Occasionally taking sample issue may differ significantly in different part of the entire population. For example, under study population consists of people living in apartments, own homes, hospitals and prisons or people living in plain regions and hill regions so in such situations the stratified sampling is one of the most commonly used approach to get a representative sample in survey sampling from different cross units of the population. The present study is set out on the recommendation of generalized variance estimators for finite population variance incorporating stratified sampling scheme with the information of single and two transformed auxiliary variables. The expressions of bias and mean square error (MSE) are obtained for the advised exponential type estimators. The conditions are obtained for which the anticipated estimators are better than the usual estimator. An empirical and simulation study is conducted to prove the superiority of the recommended estimator.

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