Synthetic populations are used to study methods for adapting Efron\u2019s bootstrap estimation technique to finite population sampling. Of particular interest is the extention of these methods to two-stage cluster sampling. Using simulations based on five artificial populations, two variations of bootstrap estimators and two Taylor series variance estimators for a ratio estimator are compared by mean square errors, stability of the variance estimators, and coverage of the confidence intervals. Generally, there appear to be small differences among the variance estimators, except the bootstrap estimators are somewhat less stable than the Taylor series estimators.[Philip J. McCarthy, Cecelia B. Snowden].Bibliography: p. 23.1985399293
Consider a finite population from which the stratified sample with simple random sample without repl...
This paper provides a method for determining the exact finite sample properties of the bootstrap. Pr...
In sampling finite populations, several resampling schemes have been proposed. The common starting p...
Bootstrap is a useful tool for making statistical inference, but it may provide erroneous results un...
We illustrate bootstrap methods in a simple example, Among ideas discussed are: basic distributional...
Resampling methods are often invoked in risk modelling when the stability of estimators of model par...
<p>The finite population bootstrap method is used as a computer-<br />intensive alternative to estim...
In complex designs, classical bootstrap methods result in a biased variance estimator when the samp...
A collection of six novel bootstrap algorithms, applied to probability-proportional-to-size samples,...
Ce mémoire propose une adaptation lisse de méthodes bootstrap par pseudo-population aux fins d'estim...
Perez and Pontius (J Stat Comput Simul 76:755-764, 2006) introduced several bootstrap methods under ...
In complex survey sampling every population unit is assigned a specific probability to be included ...
Sampling is one of the most fundamental concepts in statistics, as the quality and accuracy of the s...
A new and very fast method of bootstrap for sampling without replacement from a finite population is...
Since bootstrap samples are simple random samples with replacement from the original sample, the inf...
Consider a finite population from which the stratified sample with simple random sample without repl...
This paper provides a method for determining the exact finite sample properties of the bootstrap. Pr...
In sampling finite populations, several resampling schemes have been proposed. The common starting p...
Bootstrap is a useful tool for making statistical inference, but it may provide erroneous results un...
We illustrate bootstrap methods in a simple example, Among ideas discussed are: basic distributional...
Resampling methods are often invoked in risk modelling when the stability of estimators of model par...
<p>The finite population bootstrap method is used as a computer-<br />intensive alternative to estim...
In complex designs, classical bootstrap methods result in a biased variance estimator when the samp...
A collection of six novel bootstrap algorithms, applied to probability-proportional-to-size samples,...
Ce mémoire propose une adaptation lisse de méthodes bootstrap par pseudo-population aux fins d'estim...
Perez and Pontius (J Stat Comput Simul 76:755-764, 2006) introduced several bootstrap methods under ...
In complex survey sampling every population unit is assigned a specific probability to be included ...
Sampling is one of the most fundamental concepts in statistics, as the quality and accuracy of the s...
A new and very fast method of bootstrap for sampling without replacement from a finite population is...
Since bootstrap samples are simple random samples with replacement from the original sample, the inf...
Consider a finite population from which the stratified sample with simple random sample without repl...
This paper provides a method for determining the exact finite sample properties of the bootstrap. Pr...
In sampling finite populations, several resampling schemes have been proposed. The common starting p...