Nonparametric Hypothesis Testing: Rank and Permutation Methods with Applications in R

Appendix D R functions and codes

This appendix includes all R codes used throughout the book. It is worth noting that we used and fully recognize the validity and authorship of R codes existing in R packages and produced as complementary material for other books. Among those we refer to the following websites:

• http://static.gest.unipd.it/~salmaso/web/springerbook.htm
• http://homes.stat.unipd.it/livio/?page=software&lang=IT
• http://www.biostat.uni-hannover.de/software.html
• http://web.mit.edu/caughey/www/Site/Code.html
• http://www.wiley.com/go/npc.

Packages

Package stats (version 2.15.3)

• ansari.test(x, y, alternative = c("two.sided", "less", "greater"), exact = NULL, conf.int = FALSE, conf.level = 0.95,…)

  It performs the Ansari–Bradley two-sample test for a difference in scale parameters.

• binom.test(x, n, p = 0.5, alternative = c("two.sided", "less", "greater"), conf.level = 0.95)

  It performs an exact test on the proportion/probability of success in a Bernoulli experiment.

• chisq.test(x, y = NULL, correct = TRUE, p = rep(1/length(x), length(x)), rescale.p = FALSE,simulate.p.value = FALSE, B = 2000)

  It performs the chi-square goodness-of-fit tests for comparisons of proportions/ probabilities and for independence of categorical variables.

• cor(x, y = NULL, use = "everything", method = c("pearson", "kendall", "spearman"))

  It computes the correlation of x and y if these are vectors. If x and y are matrices then the covariances (or correlations) between the columns of x and the ...