In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outcome of the test will depend on the sequence of random numbers used to generate the bootstrap samples, and it necessarily results in some loss of power. We examine the extent of this power loss and propose a simple pretest procedure for choosing the number of bootstrap samples so as to minimize experimental randomness. Simulation experiments suggest that this procedure will work very well in practice
We first propose two procedures for estimating the rejection probabilities of bootstrap tests in Mon...
The role of detrending in bootstrap unit root tests is investigated. When bootstrap-ping, detrending...
The parametric bootstrap P-value based on a test statistic T is the exact tail probability of the ob...
In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outc...
In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outc...
In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outc...
Bootstrap tests are tests for which the signicance level is calculated using some variant of the boo...
Bootstrap tests are tests for which the significance level is calculated using some variant of the b...
The construction of bootstrap hypothesis tests can differ from that of bootstrap confidence interval...
We introduce the concept of the bootstrap discrepancy, which measures the difference in rejection pr...
In this paper we discuss three methods to apply the bootstrap correctly to hypothesis testing. For e...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
MSc (Statistics), North-West University, Potchefstroom CampusIn this study we investigate the finite...
N-of-1 study designs involve the collection and analysis of repeated measures data from an individua...
A method is presented for the estimation of the power of permutation tests when F is unknown. It is ...
We first propose two procedures for estimating the rejection probabilities of bootstrap tests in Mon...
The role of detrending in bootstrap unit root tests is investigated. When bootstrap-ping, detrending...
The parametric bootstrap P-value based on a test statistic T is the exact tail probability of the ob...
In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outc...
In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outc...
In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outc...
Bootstrap tests are tests for which the signicance level is calculated using some variant of the boo...
Bootstrap tests are tests for which the significance level is calculated using some variant of the b...
The construction of bootstrap hypothesis tests can differ from that of bootstrap confidence interval...
We introduce the concept of the bootstrap discrepancy, which measures the difference in rejection pr...
In this paper we discuss three methods to apply the bootstrap correctly to hypothesis testing. For e...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
MSc (Statistics), North-West University, Potchefstroom CampusIn this study we investigate the finite...
N-of-1 study designs involve the collection and analysis of repeated measures data from an individua...
A method is presented for the estimation of the power of permutation tests when F is unknown. It is ...
We first propose two procedures for estimating the rejection probabilities of bootstrap tests in Mon...
The role of detrending in bootstrap unit root tests is investigated. When bootstrap-ping, detrending...
The parametric bootstrap P-value based on a test statistic T is the exact tail probability of the ob...