Permutation, Parametric, and Bootstrap Tests of Hypotheses (3rd ed.)

By Eric R. Ziegel. 2005

277 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/868af9c158d6fbda983e6a1b5a4e137aa7d6c39c

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Citations in the corpus

Phase I Distribution-Free Analysis of Univariate Data (2013, methodology): “Then, significance is determined using a permutation approach (Pesarin (2001), Lehmann and Romano (2005), Good (2005)) applied to a set of statistics testing the presence of either one or multiple change points.”
Distances and inference for covariance operators (2014, methodology): “This is a common strategy for testing scale parameters, such as variance, for univariate real random variables (e.g., Good, 2005, § 3.7.2).”
Which words are hard to recognize? Prosodic, lexical, and disfluency factors that increase speech recognition error rates (2010, methodology): “10 The permutation test is a standard nonparametric test that can be used with data like ours that may not conform to any particular known distributional form (Good, 2004).”
An Introduction to Recursive Partitioning: Rationale, Application and Characteristics of Classification and Regression Trees, Bagging and Random Forests (2009, unknown): “In summary, one can conclude, in accordance with Heidema et al. (2006), that high-dimensional data should be approached by several different methods because each single method has its strengths and weaknesses: Boosting, for example, can be used for variable selection in linear and other additive mod”
Zeileis Conditional Variable Importance for Random Forests (2015, background): “It can help our understanding to consider the permutation scheme in the context of permutation tests [34]: Usually a null hypothesis is considered that implies the independence of particular (sets of) variables.”
The WTO trade effect (2011, background): “See Pesarin (2001) and Good (2004) for an introduction to the concept, and Ernst (2004) for a survey of the permutation method in general contexts. Recently, Imbens and Rosenbaum (2005) showed that confidence intervals constructed by the permutation method are far more reliable than other confidence”
Power in Voxel-based Lesion-Symptom Mapping (2007, methodology): “Similarly, Kempthorne (1955, cited by Good, 2004) wrote, ‘‘Tests of significance in the randomized experiment have frequently been presented by way of normal law theory, whereas their validity stems from randomization theory.’’”
Robust Permutation Tests For Correlation And Regression Coefficients (2017, background): “Applications of permutation tests can be found in Good (2005).”
Weighted resampling of martingale difference arrays with applications (2011, background): “Edgington and Onghena [6], Good [11] or Clark and West [3] as well as Escancianoa and Velasco [8] in the context of testing martingale differences.”