Resampling Methods: A Practical Guide to Data Analysis

By Yogendra P. Chaubey. Technometrics, 2000

559 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Sociology and Political Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/fc5b0f4d19f3dba71c7c824b5a0b96fe9f364261

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Citations in the corpus

Resampling Methods for Meta-Model Validation with Recommendations for Evolutionary Computation (2012, background): “Jin (2005), Tenne and Armfield (2008), Knowles and Nakayama (2008), Nakayama et al.”
Does Professor Quality Matter? Evidence from Random Assignment of Students to Professors (2010, unknown): “Although the placement algorithm used by the USAFA registrar should create sections that are a random sample of the course population with respect to academic ability, we employed resampling techniques as in Lehmann and Romano (2005) and Good (2006) to empirically test this assumption.”
Contemporary approaches to assessing mediation in communication research. (2008, methodology): “…are unrealistic, to computationally intensive methods such as bootstrapping, as these methods typically make fewer unwarranted assumptions and, as a result, can produce more accurate inference (see, e.g., Efron & Tibshirani, 1998; Good, 2001; Lunneborg, 2000; Mooney & Duval, 1993; Rodgers, 1999).”
Probabilistic Approach to the Identification of Input Variables to Estimate Hydraulic Conductivity (2008, methodology): “We used the jackknife cross-validation (randomized subset selection without replacement or “bagging”) to generate each of those data sets (Good, 1999).”
Percentage of All Non-Overlapping Data (PAND) (2007, background): “Failure to meet data assumptions can sometimes be addressed by data transformations or resampling/bootstrapping methodologies (Davison & Hinkley, 1997; Good, 2001).”
A mixture model approach for the analysis of microarray gene expression data (2002, unknown): “…again recommend use of a bootstrap test rather than a permutation test or traditional non-parametric test such as the Mann–Whitney U or Kruskal–Wallace tests because, unlike these latter tests, the bootstrap need not assume homogeneity of variance (Good, 1999) and is therefore less restrictive.”
Statistical phylogeography: methods of evaluating and minimizing inference errors (2004, methodology): “Cross-validation is a common tool in the general statistical literature (Good 1999) for achieving validation of specific inferences.”
ARCHITECTURE OF PLANETARY SYSTEMS BASED ON KEPLER DATA: NUMBER OF PLANETS AND COPLANARITY (2012, methodology): “Given that some higher-j categories in our multiplicity vector may have low numbers, we performed a second calculation of the chisquare probability using a more robust randomization method (e.g., Good 2006).”
Regulation of anti‐herbivore defence by Fucus vesiculosus in response to various cues (2004, methodology): “, Arlington, VA, USA) (Bärlocher 1999; Good 1999).”
Why do chimpanzees hunt and share meat (2001, methodology): “To generate an expected distribution of deviations, we employed a resampling technique based on our original observations (Good 1999).”