Results Citations. Citation Type. Has PDF. Publication Type. More Filters. Resampling student'st-type statistics. The present paper establishes conditional and unconditional central limit theorems for various resampling procedures for thet-statistic.
The results work under fairly general conditions and the … Expand. The present paper establishes conditional and unconditional central limit theorems for various resampling procedures for the t-statistic.
View 20 excerpts, cites background and methods. Tests of independence by bootstrap and permutation : an asymptotic and non-asymptotic study.
Application to neurosciences. On the one hand, we construct such tests based on bootstrap and permutation approaches. Their asymptotic performance are studied in a point process framework through the analysis of the asymptotic … Expand. Minimax optimality of permutation tests.
Permutation tests are widely used in statistics, providing a finite-sample guarantee on the type I error rate whenever the distribution of the samples under the null hypothesis is invariant to some … Expand. View 1 excerpt, cites background. On the other hand, when comparing or testing particular … Expand. View 1 excerpt, cites results.
Multivariate and multiple permutation tests. In this article, we consider the use of permutation tests for comparing multivariate parameters from two populations. First, the underlying properties of permutation tests when comparing parameter … Expand.
Asymptotically valid and exact permutation tests based on two-sample U-statistics. Abstract The two-sample Wilcoxon test has been widely used in a broad range of scientific research, including economics, due to its good efficiency, robustness against parametric distributional … Expand.
Permutation test for the multivariate coefficient of variation in factorial designs. New inference methods for the multivariate coefficient of variation and its reciprocal, the standardized mean, are presented. While there are various testing procedures for both parameters in the … Expand. The two-sample problem for Poisson processes: adaptive tests with a non-asymptotic wild bootstrap approach.
Considering two independent Poisson processes, we address the question of testing equality of their respective intensities. We first propose single tests whose test statistics are U-statistics based … Expand.
View 1 excerpt, cites methods. However, … Expand. On the Asymptotic Theory of Permutation Statistics. In this paper limit theorems for the conditional distributions of linear test statistics are proved.
The assertions are conditioned by the sigma-field of permutation symmetric sets. Limit theorems … Expand. Either asymptotic theory or bootstrap … Expand. I rarely see them as competitors on the same problem, and have used them on different real problems -- often there will be a natural choice of which to look at.
There are benefits to both, but neither in a panacaea. If you're hoping to reduce learning effort by focusing on only one of them you're likely to be disappointed -- both are essential parts of the resampling toolbox. Sign up to join this community. The best answers are voted up and rise to the top. Stack Overflow for Teams — Collaborate and share knowledge with a private group.
Create a free Team What is Teams? Learn more. Bootstrap vs. Asked 9 years, 10 months ago. Active 1 year, 5 months ago. Viewed 38k times. Improve this question. Jessica Burnett 1 1 silver badge 8 8 bronze badges. Judging by the number of citations customers , McDonalds is a far more popular better? Will you take your next seminar speaker to McDonalds, then? Add a comment. Active Oldest Votes. Improve this answer. Josh O'Brien 2 2 silver badges 13 13 bronze badges.
Greg Snow Greg Snow Why is the bootstrap confidence interval less powerful than the permutation test? How much so? Can one characterize the situations under which it is significantly less powerful?
It seems an advantage to be able to show a confidence interval, so in that sense the bootstrap seems more valuable. See this answer: stats. Patrick Burns Patrick Burns 1, 7 7 silver badges 6 6 bronze badges. With independence and under a null of no effects at all, the observations are exchangeable and you can therefore test that hypothesis but you don't have a way to construct a permutation test of just the factors since you expect the covariate to have an effect and testing it being null isn't interesting ; similarly you can't construct a permutation test of just one of the two factors.
There's an obvious exchangeable quantity if you know the population coefficients you aren't testing and the errors would always be exchangeable but you can't observe those things. If you substitute estimates of the coefficients or of the errors i. However under some particular conditions they would be approximately exchangeable some people advocate doing precisely this I suspect there something deeper for me to learn here.
For a starting point, some of the references here should do: davegiles. Show 3 more comments. Sign up or log in Sign up using Google. Sign up using Facebook.
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