Applications to Sample Surveys. Lezersrecensies 1 Vond u deze recensie nuttig? Usually the jackknife is easier to apply to complex sampling schemes than the bootstrap. Category Portal Commons WikiProject. Monte Carlo methods Statistical inference Resampling statistics Nonparametric statistics. The two key differences to the bootstrap are:
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Journal of the American Statistical Association. When sample sizes are very large, the Pearson's chi-square test will give accurate results. Usually the jackknife is easier to apply to complex sampling schemes than the bootstrap.
Introduction to Variance Estimation Second ed. Theory and Methods Peter J.
Permutation tests are a subset of non-parametric statistics. It is often used as a robust alternative to inference based on parametric assumptions when those assumptions are in doubt, or where jacjknife inference is impossible or requires very complicated formulas for the calculation of standard errors.
The bootstrap allows to replace the samples with low weights by copies of the samples with high weights. Because of this, the jackknife is popular when the estimates need to be verified several times before publishing e.
The Jackknife and Bootstrap : Jun Shao :
The test proceeds as follows. In statisticsresampling is any of a variety of thee for doing one of the following:. For many statistical parameters the jackknife estimate of variance tends asymptotically to the true value almost surely. The Jackknife and Bootstrap. Sampling stratified cluster Standard error Opinion poll Questionnaire.
Resampling (statistics) - Wikipedia
Grouped data Frequency distribution Contingency table. Pitman in the s. Bayesian Bootstrap and Booystrap Weighting. Principal Component Analysis Ian T. Annals of Mathematical Statistics. Agenda Seminars Masterclasses e-learning Sprekers Incompany.
On the other hand, when this verification feature is not crucial and it is of interest not to have a number but just an idea of its distribution, the bootstrap is preferred e. The two key differences to the bootstrap are: It may also be used for constructing hypothesis tests. Aad Jackknif Der Vaart. An important consequence of this assumption is that tests of difference in location like a permutation t-test require equal variance.
Pearson product-moment correlation Rank correlation Spearman's rho Kendall's tau Partial correlation Scatter plot. The theoretical properties of the jackknife and bootstrap methods are studied in this book in an asymptotic framework.
Applications to Linear Models. This is done by generating the reference distribution by Monte Carlo samplingwhich takes a small relative to the total number of permutations random sample of the possible replicates. This can be enough for basic statistical inference e.
Applications to Sample Surveys.
The Jackknife and Bootstrap
Journal of the Royal Statistical Society. Theorems are illustrated by examples.
Lezersrecensies 1 Vond u deze recensie nuttig? Please improve this article by removing less relevant or redundant publications with the same point of view ; or by incorporating the relevant publications into the body of the article through appropriate citations.
In addition to the theory for the jackknife and bootstrap methods in problems with independent and identically distributed Li. While subsampling was originally proposed for the case of independent and identically distributed iid data only, the jacjknife has been extended to cover time series data as well; in this case, one resamples blocks of subsequent data rather than individual data points.
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