Publication date
January 2012
DOI Publisher
Informa UK Limited ISSN
0361-0918 Citation count (estimate)
1Abstract
10.1080/03610918.2012.625333Communications in Statistics: Simulation and Computation416865-87
10.1080/03610918.2012.625333Communications in Statistics: Simulation and Computation416865-87
The following paper details how the use of simulation can help to introduce computer intensive appli...
The.632 error estimator is a bias correction of the bootstrap estimator which leads to an underestim...
The bootstrap is a powerful non-parametric statistical technique for making probability-based infere...
The bootstrap is a simple but versatile technique for the statistical analysis of random simulations...
The Bootstrap is the most widely used resampling statistical method. This method becomes very popula...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
Bootstrap methods provide a powerful approach to statistical data analysis, as they have more genera...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
Bootstrapping techniques have become increasingly popular in applied econometrics and other areas. T...
The bootstrap, extensively studied during the last decade, has become a powerful tool in different a...
Bootstrap methods involve estimating a model many times using simulated data. Then quantities comput...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
This tutorial considers some very general procedures for analysing the results of a simulation exper...
grantor: University of TorontoThe bootstrap was introduced in 1979 as a computer-intensive...
Abstract. In applied econometrics, the researcher typically has two recourses for conducting inferen...
The following paper details how the use of simulation can help to introduce computer intensive appli...
The.632 error estimator is a bias correction of the bootstrap estimator which leads to an underestim...
The bootstrap is a powerful non-parametric statistical technique for making probability-based infere...
The bootstrap is a simple but versatile technique for the statistical analysis of random simulations...
The Bootstrap is the most widely used resampling statistical method. This method becomes very popula...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
Bootstrap methods provide a powerful approach to statistical data analysis, as they have more genera...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
Bootstrapping techniques have become increasingly popular in applied econometrics and other areas. T...
The bootstrap, extensively studied during the last decade, has become a powerful tool in different a...
Bootstrap methods involve estimating a model many times using simulated data. Then quantities comput...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
This tutorial considers some very general procedures for analysing the results of a simulation exper...
grantor: University of TorontoThe bootstrap was introduced in 1979 as a computer-intensive...
Abstract. In applied econometrics, the researcher typically has two recourses for conducting inferen...
The following paper details how the use of simulation can help to introduce computer intensive appli...
The.632 error estimator is a bias correction of the bootstrap estimator which leads to an underestim...
The bootstrap is a powerful non-parametric statistical technique for making probability-based infere...
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