Tag: Bootstrap and Resampling

Rick Wicklin 0
The smooth bootstrap method in SAS

Last week I showed how to use the simple bootstrap to randomly resample from the data to create B bootstrap samples, each containing N observations. The simple bootstrap is equivalent to sampling from the empirical cumulative distribution function (ECDF) of the data. An alternative bootstrap technique is called the smooth

Rick Wicklin 0
Four essential sampling methods in SAS

Many simulation and resampling tasks use one of four sampling methods. When you draw a random sample from a population, you can sample with or without replacement. At the same time, all individuals in the population might have equal probability of being selected, or some individuals might be more likely

Rick Wicklin 0
Resampling and permutation tests in SAS

My colleagues at the SAS & R blog recently posted an example of how to program a permutation test in SAS and R. Their SAS implementation used Base SAS and was "relatively cumbersome" (their words) when compared with the R code. In today's post I implement the permutation test in

Rick Wicklin 0
Permute elements within each row of a matrix

Bootstrap methods and permutation tests are popular and powerful nonparametric methods for testing hypotheses and approximating the sampling distribution of a statistic. I have described a SAS/IML implementation of a bootstrap permutation test for matched pairs of data (an alternative to a matched-pair t test) in my paper "Modern Data

Rick Wicklin 0
Sample without replacement in SAS

Last week I showed three ways to sample with replacement in SAS. You can use the SAMPLE function in SAS/IML 12.1 to sample from a finite set or you can use the DATA step or PROC SURVEYSELECT to extract a random sample from a SAS data set. Sampling without replacement

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