Add to ORKGAbstract This paper presents a comparison of the nonparametric and parametric bootstrap methods, when the statistic of interest is the sample variance estimator. Conditions when the nonparametric bootstrap method of variance performs better than the parametric bootstrap method are described
The paper is devoted to highly robust statistical estimators based on implicit weighting, which have...
This paper compares different versions of the multiple variance ratio test based on bootstrap techni...
Variance estimation techniques for nonlinear statistics, such as ratios and regression and correlati...
This thesis describes and compares some of commonly used methods of variance estimation of various s...
Consider a finite population from which the stratified sample with simple random sample without repl...
ObjectiveThe purpose of this study is to compare the performance of the four estimation methods (tra...
Not Availablea new boot~trap technique of variance estimation for complex survey data known as "Res...
The purpose of this paper was to investigate the performance of the parametric bootstrap data genera...
ObjectiveThe purpose of this study is to compare the performance of the four estimation methods (tra...
While various robust regression estimators are available for the standard linear regression model, p...
For estimation of parameters of a multi-level model fitted to hierarchical survey data, the standard...
The Rao-Wu bootstrap variance estimation method is frequently used at Statistics Canada. It is simpl...
AbstractWe describe a bootstrap method for estimating mean squared error and smoothing parameter in ...
The purpose of this study was to develop a sngle procedure for comparing population variances which ...
The paper contains a description of four different block bootstrap methods, i.e., non-overlapping bl...
The paper is devoted to highly robust statistical estimators based on implicit weighting, which have...
This paper compares different versions of the multiple variance ratio test based on bootstrap techni...
Variance estimation techniques for nonlinear statistics, such as ratios and regression and correlati...
This thesis describes and compares some of commonly used methods of variance estimation of various s...
Consider a finite population from which the stratified sample with simple random sample without repl...
ObjectiveThe purpose of this study is to compare the performance of the four estimation methods (tra...
Not Availablea new boot~trap technique of variance estimation for complex survey data known as "Res...
The purpose of this paper was to investigate the performance of the parametric bootstrap data genera...
ObjectiveThe purpose of this study is to compare the performance of the four estimation methods (tra...
While various robust regression estimators are available for the standard linear regression model, p...
For estimation of parameters of a multi-level model fitted to hierarchical survey data, the standard...
The Rao-Wu bootstrap variance estimation method is frequently used at Statistics Canada. It is simpl...
AbstractWe describe a bootstrap method for estimating mean squared error and smoothing parameter in ...
The purpose of this study was to develop a sngle procedure for comparing population variances which ...
The paper contains a description of four different block bootstrap methods, i.e., non-overlapping bl...
The paper is devoted to highly robust statistical estimators based on implicit weighting, which have...
This paper compares different versions of the multiple variance ratio test based on bootstrap techni...
Variance estimation techniques for nonlinear statistics, such as ratios and regression and correlati...