Topic
Resampling
About: Resampling is a research topic. Over the lifetime, 5428 publications have been published within this topic receiving 242291 citations.
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TL;DR: This paper describes a MATLAB script, located on the IAMG server, that calculates descriptive statistics and performs inference on azimuthal parameters and includes tests for specific distributions, and tests on the preferred direction and concentration of vectors about this direction.
52 citations
TL;DR: In this article, the point patterns are divided into disjoint quadrats, on each of which an estimate of Ripley's K-function is calculated, and the two groups of empirical K-functions are compared by a permutation test using a Studentized test statistic.
Abstract: In this study, a new test is proposed for the hypothesis that two (or more) observed point patterns are realizations of the same spatial point process model To this end, the point patterns are divided into disjoint quadrats, on each of which an estimate of Ripley’s K-function is calculated The two groups of empirical K-functions are compared by a permutation test using a Studentized test statistic The proposed test performs convincingly in terms of empirical level and power in a simulation study, even for point patterns where the K-function estimates on neighboring subsamples are not strictly exchangeable It also shows improved behavior compared with a test suggested by Diggle et al for the comparison of groups of independently replicated point patterns In an application to two point patterns from pathology that represent capillary positions in sections of healthy and cancerous tissue, our Studentized permutation test indicates statistical significance, although the patterns cannot be clearly distin
52 citations
TL;DR: The Fisher-Pitman permutation test is shown to possess significant advantages over conventional alternatives when analyzing differences among independent samples with unequal variances.
Abstract: The Fisher-Pitman permutation test is shown to possess significant advantages over conventional alternatives when analyzing differences among independent samples with unequal variances.
52 citations
TL;DR: This procedure provides an alternative to the finite element method for the computation of effective thermal conductivity and a randomised resampling procedure has been designed in order to choose the best estimation model from a statistical point of view.
51 citations
TL;DR: In this paper, a sieve bootstrap procedure based on residual resampling from autoregressive approximations is used to test the unit root hypothesis in models that may include a linear rend and/or an intercept.
Abstract: This paper examines bootstrap tests of the null hypothesis of an autoregressive unit root in models that may include a linear rend and/or an intercept and which are driven by innovations that belong to the class of stationary and invertible linear processes. Our approach makes use of a sieve bootstrap procedure based on residual resampling from autoregressive approximations, the order of which increases with the sample size at a suitable rate. We show that the sieve bootstrap provides asymptotically valid tests of the unit-root hypothesis and demonstrate the small-sample effectiveness of the method by means of simulation.
51 citations