R2sample

NEWS code{white-space: pre-wrap;} span.smallcaps{font-variant: small-caps;} span.underline{text-decoration: underline;} div.column{display: inline-block; vertical-align: top; width: 50%;} div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;} ul.task-list{list-style: none;} R2sample 4.1.0 User supplied routine can now also return p value for twosample_power Some other minor changes R2sample 4.0.1 Fixed a serious bug in twosample_test R2sample 4.0.0 It is now possible to use a routine to generate new simulated data to find p values, the parametric bootstrap approach. This is needed for the goodness-of-fit/twosample hybrid problem. Also some changes to the hidden interior routines R2sample 3.1.1 Fixed a minor bug R2sample 3.1.0 Improved the routines that do power calculations for better speed. Included a timing routine to see whether using a single core is faster than using multiple processing. Some minor changes to other routines. R2sample 3.0.0 Added routine to allow benchmarking of new user supplied tests. Some minor changes to other routines. R2sample 2.2.0 some minor bug fixes, additions to vignette R2sample 2.1.0 Added routines for calculating p values adjusted for simultaneous testing R2sample 1.1.0 fixed a bug in calculation of chi square test, made cpp routines invisible, fixed issue with help titles R2sample 1.0.0 fixed a code problem in TS_disc_cpp on line 146 made some changes to the arguments of twosample_power R2sample 0.0.4 changed line 66 in TS_cont_cpp.cpp from while ( (x[j]<=sxy[i]) && (j<nx)) to while ( (j<nx) && (x[j]<=sxy[i]) ) to avoid heap-buffer-overflow error. R2sample 0.0.3 Changed & to && in a TS_cont_cpp.cpp R2sample 0.0.2 Changed | to || in a number of the C++ routines per request from the CRAN Team R2sample 0.0.1 Added a NEWS.md file to track changes to the package. Oct 10, 2022: Added to run_shiny(), added () to function names eliminated \dontrun(), added toy examples changed cat to message changed Maintainer to Authors@R Oct. 11, 2022: Eliminated all and , added toy examples Searched and eliminated all empty spaces in DESCRIPTION that I could find.

Help for package R2sample const macros = { "\\R": "\\textsf{R}", "\\mbox": "\\text", "\\code": "\\texttt"}; function processMathHTML() { var l = document.getElementsByClassName('reqn'); for (let e of l) { katex.render(e.textContent, e, { throwOnError: false, macros }); } return; } Package {R2sample} Contents R2sample-package Cpporder TS_cont TS_disc TSw_cont TSw_disc asymptotic_pvalues bincounter calcTS case.studies chi_power chi_test gen_cont_noweights gen_cont_weights gen_disc gen_sim_data myTS2 plot_power powerC powerR power_cont_LS power_newtest power_studies_results pvaluecdf repC run.studies run_shiny signif.digits testC test_methods timecheck twosample_power twosample_test twosample_test_adjusted_pvalue wbincounter weights Title: Various Methods for the Two Sample Problem Version: 4.1.0 Description: The routine twosample_test() in this package runs the two sample test using various test statistic. The p values are found via permutation or large sample theory. The routine twosample_power() allows the calculation of the power in various cases, and plot_power() draws the corresponding power graphs. The routine run.studies allows a user to quickly study the power of a new method and how it compares to some of the standard ones. License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] Encoding: UTF-8 RoxygenNote: 7.3.2 LinkingTo: Rcpp Imports: Rcpp, parallel, shiny, ggplot2, stats, graphics, microbenchmark Suggests: rmarkdown, knitr, testthat (≥ 3.0.0) VignetteBuilder: knitr Depends: R (≥ 3.5) LazyData: true NeedsCompilation: yes Packaged: 2025-06-16 18:11:44 UTC; Wolfgang Author: Wolfgang Rolke [aut, cre] Maintainer: Wolfgang Rolke <wolfgang.rolke@upr.edu> Repository: CRAN Date/Publication: 2025-06-16 18:30:06 UTC R2sample: Various Methods for the Two Sample Problem Description The routine twosample_test() in this package runs the two sample test using various test statistic. The p values are found via permutation or large sample theory. The routine twosample_power() allows the calculation of the power in various cases, and plot_power() draws the corresponding power graphs. The routine run.studies allows a user to quickly study the power of a new method and how it compares to some of the standard ones. Author(s) Maintainer : Wolfgang Rolke wolfgang.rolke@upr.edu ( ORCID ) sort vector y by values in vector x Description sort vector y by values in vector x Usage Cpporder(y, x) Arguments y numeric vector x numeric vector Value numeric vector find test statistics for continuous data Description find test statistics for continuous data Usage TS_cont(x, y) Arguments x first continuous data set y second continuous data set Value A vector of test statistics find test statistics for discrete data Description find test statistics for discrete data Usage TS_disc(x, y, vals, ADweights = as.numeric(c(2))) Arguments x integer vector of data set 1 y integer vector of data set 2 vals numeric vector of values of discrete data set ADweights A vector of weights for AD method Value A vector of test statistics find test statistics for continuous data with weights Description find test statistics for continuous data with weights Usage TSw_cont(x, y, wx, wy) Arguments x first continuous data set y second continuous data set wx weights of x wy weights of y Value A vector of test statistics Find test statistics for weighted discrete data Description Find test statistics for weighted discrete data Usage TSw_disc(x, y, vals, wx, wy) Arguments x integer vector of counts y integer vector of counts vals A numeric vector with the values of the discrete rv. wx integer vector of weights wy integer vector of weights Value A vector with test statistics This function finds the p values of several tests based on large sample theory Description This function finds the p values of several tests based on large sample theory Usage asymptotic_pvalues(x, n, m) Arguments x a vector of test statistics n size of sample 1 m size of sample 2 Value A vector of p values. find counts in bins. Useful for power calculations. Replaces hist command from R. Description find counts in bins. Useful for power calculations. Replaces hist command from R. Usage bincounter(x, bins) Arguments x numeric vector bins numeric vector Value Integer vector of counts This function calculates the test statistics for continuous data Description This function calculates the test statistics for continuous data Usage calcTS(dta, TS, typeTS, TSextra) Arguments dta data set TS routine typeTS format of TS TSextra list passed to TS function Value A vector of numbers This function creates the functions needed to run the various case studies. Description This function creates the functions needed to run the various case studies. Usage case.studies(which, nsample = 500) Arguments which name of the case study. nsample =500, sample size. Value a list of functions This function runs the chi-square test for continuous or discrete data Description This function runs the chi-square test for continuous or discrete data Usage chi_power( rxy, alpha = 0.05, B = 1000, xparam, yparam, nbins = c(50, 10), minexpcount = 5, typeTS ) Arguments rxy a function to generate data alpha =0.05 type I error probability of test B =1000 number of simulation runs xparam vector of parameter values yparam vector of parameter values nbins =c(50, 10) number of desired bins minexpcount =5 smallest number of counts required in each bin typeTS type of problem, continuous/discrete, with/without weights Value A matrix of power values This function runs the chi-square test for continuous or discrete data Description This function runs the chi-square test for continuous or discrete data Usage chi_test(dta, nbins = c(50, 10), minexpcount = 5, typeTS, ponly = FALSE) Arguments dta a list with two elements for continuous data or three elements for discrete data, Can also include weights for continuous data nbins =c(50, 10) number of desired bins minexpcount =5 smallest number of counts required in each bin typeTS =5 type of problem, continuous/discrete, with/without weights ponly Should the p value alone be returned? Value A list with the test statistics, the p value and the degree of freedom for each test simulate continuous data without weights Description simulate continuous data without weights Usage gen_cont_noweights(x, y, TSextra) Arguments x first data set y second data set TSextra extra stuff Value A list of permuted vectors simulate continuous data with weights Description simulate continuous data with weights Usage gen_cont_weights(x, y, wx, wy, TSextra) Arguments x first data set y second data set wx weights of first data set wy weights of second data set TSextra extra stuff Value A list of permuted vectors simulate new discrete data Description simulate new discrete data Usage gen_disc(dtax, dtay, vals, TSextra) Arguments dtax first data set, counts dtay second data set, counts vals values of discrete random variable TSextra extra stuff Value A list of permuted vectors simulate continuous data without weights Description simulate continuous data without weights Usage gen_sim_data(dta, TSextra) Arguments dta data set TSextra extra stuff Value A list of permuted vectors a local function needed for the vignette Description a local function needed for the vignette Usage myTS2(x, y, vals) Arguments x An integer vector. y An integer vector. vals A numeric vector with the values of the discrete rv. Value A vector with test statistics This function draws the power graph, with curves sorted by the mean power and smoothed for easier reading. Description This function draws the power graph, with curves sorted by the mean power and smoothed for easier reading. Usage plot_power(pwr, xname = " ", title = " ", Smooth = TRUE, span = 0.25) Arguments pwr a matrix of power values, usually from the twosample_power command xname Name of variable on x axis title (Optional) title of graph Smooth =TRUE lines are smoothed for easier reading span =0.25bandwidth of smoothing method Va