P.Mean >> Category >> Resampling methods (created 2008-07-18). 

These pages cover resampling methods and other closely related topics like the bootsrap. Resampling is a very simple approach that offers solutions to many problems with very few assumptions about the data. These methods require a lot of computing power and have become increasingly prominent as computers have become faster. Also see Category: Adverse events in clinical trials, Category: Bayesian statistics. There is no other directly comparable page on the StATS website, but some of the topics listed under the unusual data page are relevant.

2008

P.Mean: Software for bootstrap and resampling (created 2008-07-18). Someone asked me what software they should use as they were learning how to use the bootstrap and resampling methods.

Outside resources:

P. Adam Kelly. Overview of Computer-Intensive Statistics. Excerpt: "Resampling procedures, also commonly referred to as computer intensive statistical inference procedures, may be used to assess the significance of a statistic in a hypothesis test or to determine the lower and upper bounds for a confidence interval when the usual assumptions of parametric statistical procedures are not met (Manly, 1991). Computer intensive procedures require the recomputation of hundreds or thousands of artificially constructed data sets. Like other nonparametric statistical procedures, these procedures existed as theory on paper long before they were brought into the practical mainstream. The Monte Carlo method of resampling, for example, was introduced by Barnard in 1963 (Noreen, 1989), but at that time could only be illustrated and implemented operationally on very small sample sizes. However, with the advent of fast, inexpensive computing, essentially since around 1990, the use of computer intensive procedures has grown dramatically, particularly in the area of basic academic research. Actually, with the widespread availability of powerful personal computers and statistical software that even brings resampling-type methods right into the home, the name computer intensive seems today to be as anachronistic as it was descriptive just a few years ago." [Accessed March 4, 2009]. Available at: http://www.hsrd.houston.med.va.gov/AdamKelly/resampling.html.

David C. Howell. Resampling Statistics: Randomization and the Bootstrap. Excerpt: "This set of pages is intended to serve two purposes. On the one hand, it was written to accompany a set of Windows© programs that I have written. The main program is named Resampling.exe, and is available on disk and can be downloaded from www.uvm.edu/~dhowell/StatPages/Resampling/ResamplingPackage .zip. The second purpose of these pages is to elaborate on resampling techniques and the theory behind them. " [Accessed December 5, 2009]. Available at: http://www.uvm.edu/~dhowell/StatPages/Resampling/Resampling.html.

Julian L. Simon. Resampling: The New Statistics. Excerpt: "This text grew out of chapters in the 1969 edition of Basic Research Methods in Social Science by the same author, and contains the first published example of what was later called the bootstrap. Simon is best known for his research in demography, population and the economics of natural resources, and gained fame when the noted biologist Paul Ehrlich selected five commodities and bet Simon that scarcity would drive their prices up over the period of the bet (in fact, their prices all dropped). Resampling: The New Statistics contains a number of examples in Resampling Stats, a computer program originated by Simon, but can be read on its own without the program." [Accessed December 5, 2009]. Available at: http://www.resample.com/content/text/index.shtml.

Creative Commons License All of the material above this paragraph is licensed under a Creative Commons Attribution 3.0 United States License. This page was written by Steve Simon and was last modified on 2010-04-12. There is no comparable material from my old website.

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