Add to ORKGBootstrap distribution-free resampling technique (Efron, 1979) is frequently used to assess the variance of estimators or to produce tolerance areas on visualizatio
This paper empirically and systematically assessed the performance of bootstrap resampling procedure...
The bootstrap method is a well-known method to gather a full probability distribution from the datas...
We will study here different resampling procedures for creating confidence sets in linear models. A ...
This tutorial considers some very general procedures for analysing the results of a simulation exper...
Bootstrap resampling is an extremely practical and effective way of studying the distributional prop...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
The operation of resampling from a bootstrap resample, encountered in applications of the double boo...
This paper contains a comparison of in-sample and out-of-sample performances between the resampled e...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
The Bootstrap is the most widely used resampling statistical method. This method becomes very popula...
Since its invention, Efron’s bootstrap resampling approach has changed all the aspects of statistica...
Resampling methods are a common measure to estimate the variance of a statistic of interest when dat...
Resampling methods are a common measure to estimate the variance of a statistic of interest when dat...
Resampling methods are a common measure to estimate the variance of a statistic of interest when dat...
Resampling methods are a common measure to estimate the variance of a statistic of interest when dat...
This paper empirically and systematically assessed the performance of bootstrap resampling procedure...
The bootstrap method is a well-known method to gather a full probability distribution from the datas...
We will study here different resampling procedures for creating confidence sets in linear models. A ...
This tutorial considers some very general procedures for analysing the results of a simulation exper...
Bootstrap resampling is an extremely practical and effective way of studying the distributional prop...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
The operation of resampling from a bootstrap resample, encountered in applications of the double boo...
This paper contains a comparison of in-sample and out-of-sample performances between the resampled e...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
The Bootstrap is the most widely used resampling statistical method. This method becomes very popula...
Since its invention, Efron’s bootstrap resampling approach has changed all the aspects of statistica...
Resampling methods are a common measure to estimate the variance of a statistic of interest when dat...
Resampling methods are a common measure to estimate the variance of a statistic of interest when dat...
Resampling methods are a common measure to estimate the variance of a statistic of interest when dat...
Resampling methods are a common measure to estimate the variance of a statistic of interest when dat...
This paper empirically and systematically assessed the performance of bootstrap resampling procedure...
The bootstrap method is a well-known method to gather a full probability distribution from the datas...
We will study here different resampling procedures for creating confidence sets in linear models. A ...