Multi-aspect permutation tests in shape analysis with small sample size

DOI10.1016/j.csda.2009.05.010zbMath1453.62054OpenAlexW2063854828MaRDI QIDQ961881

Chiara Brombin, Luigi Salmaso

Publication date: 1 April 2010

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2009.05.010

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Computational methods for problems pertaining to statistics (62-08) Nonparametric hypothesis testing (62G10)

Related Items (14)

Evaluation and prediction of polygon approximations of planar contours for shape analysis ⋮ Nonparametric combination-based tests in dynamic shape analysis ⋮ Permutation testing for goodness-of-fit and stochastic ordering with multivariate mixed variables ⋮ Bootstrapping and permuting paired \(t\)-test type statistics ⋮ Testing equality of correlation coefficients in two populations via permutation methods ⋮ Nonparametric bootstrap tests of conditional independence in two-way contingency tables ⋮ Multi-aspect local inference for functional data: analysis of ultrasound tongue profiles ⋮ An exact permutation method for testing any effect in balanced and unbalanced fixed effect ANOVA ⋮ Improving power of multivariate combination-based permutation tests ⋮ Dependence aliasing and the control of family-wise error rate in multiple hypothesis testing ⋮ Model-free two-sample test for network-valued data ⋮ The permutation testing approach: a review ⋮ Multi-Aspect Procedures for Paired Data with Application to Biometric Morphing ⋮ Dependency and truncated forms of combinations in multivariate combination-based permutation tests and ordered categorical variables

Uses Software

• R
• MULTTEST
• TpsDig2

Cites Work

• Multiple aspect testing for case-control designs
• An almost exact solution for the multivariate Behrens-Fisher problem
• Extending permutation conditional inference to unconditional ones
• Permutation tests. A practical guide to resampling methods for testing hypotheses.
• Nonparametric iterated combined tests for genetic differentiation
• Statistical analysis of shape through triangulation of landmarks: A study of sexual dimorphism in hominids
• Pivotal Bootstrap Methods fork-Sample Problems in Directional Statistics and Shape Analysis
• Statistical analysis of shape of objects based on landmark data.
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