Various Methods for the Two Sample Problem
This function finds the p values of several tests based on large sampl...
find counts in bins. Useful for power calculations. Replaces hist comm...
This function calculates the test statistics for continuous data
This function creates the functions needed to run the various case stu...
This function runs the chi-square test for continuous or discrete data
This function runs the chi-square test for continuous or discrete data
sort vector y by values in vector x
simulate continuous data without weights
simulate continuous data with weights
simulate new discrete data
simulate continuous data without weights
a local function needed for the vignette
This function draws the power graph, with curves sorted by the mean po...
Find the power of various discrete tests via permutation.
Power for tests with p values
Find the power of various continuous tests via simutation or permutati...
Find the power of two sample tests using Rcpp and parallel computing.
R2sample: Various Methods for the Two Sample Problem
cpp version of R routine rep
Runs the shiny app associated with R2sample package
Power Comparisons
This function does some rounding to nice numbers
This function checks whether the correct methods have been requested
run test using either simulation or permutation.
test function
find test statistics for continuous data
find test statistics for discrete data
find test statistics for continuous data with weights
Find test statistics for weighted discrete data
Power estimation for two-sample methods
Adjusted p values for simultaneous testing in the two-sample problem.
Tests for the univariate two-sample problem
Find counts and/or sum of weights in bins. Useful for power calculatio...
find weights for several statistics for discrete data
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.