calcFx: Empirical distribution function of p-values.
In PoweR: Computation of Power and Level Tables for Hypothesis Tests

Description Usage Arguments Details Value Author(s) References See Also Examples

This function computes, at given points, the value of the empirical distribution function of a sample of p-values.

1 2	calcFx(pval.mat, x = c(seq(0.001, 0.009, by = 0.001), seq(0.01, 0.985,by = 0.005), seq(0.99, 0.999, by = 0.001)))

`pval.mat`	matrix whose each column contains a vector of p-values for a given test statistic. The column names of this matrix should be set to the names of the various test statistics considered, whereas the rownames should all be set to the name of the distribution under which the p-values have been computed. This matrix can be obtained using function `many.pval`.
`x`	vector of points at which to evaluate the empirical distribution function.

See equation (2) in Lafaye de Micheaux and Tran (2014).

An object of class Fx is returned, which contains a list whose components are:

`Fx.mat`	matrix whose ith column contains the values of the empirical distribution function (evaluated at the points in vector `x`) of the p-values of the ith test statistic.
`x`	same vector `x` as input.
`law`	name of the distribution under which the p-values have been computed. Should correspond to the row names of `pval.mat`.
`statnames`	names of the test statistics. Should correspond to the column names of `pval.mat`.
`N`	number of p-values used.

P. Lafaye de Micheaux, V. A. Tran

Pierre Lafaye de Micheaux, Viet Anh Tran (2016). PoweR: A Reproducible Research Tool to Ease Monte Carlo Power Simulation Studies for Goodness-of-fit Tests in R. Journal of Statistical Software, 69(3), 1–42. doi:10.18637/jss.v069.i03

many.pval, plot.pvalue, plot.discrepancy, plot.sizepower

stind <- c(43, 44, 42)   # Indices of test statistics.
alter <-list(stat43 = 3, stat44 = 3, stat42 = 3) # Type for each test.
# Several p-values computed under the null.
pnull <- many.pval(stat.indices = stind, law.index = 1,
                        n = 100, M = 10, N = 10, alter = alter,
                        null.dist = 1,
                        method = "direct")$pvals
xnull <- calcFx(pnull)