graph: p-value plot, p-value discrepancy plot and size-power curves.

In PoweR: Computation of Power and Level Tables for Hypothesis Tests

Description

This function draws a p-value plot, a p-value discrepancy plot or a size-power curves plot.

Usage

graph(matrix.pval, xi = 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)),
      type = c("pvalue.plot", "pvalue.discrepancy", "size.power"),
      center = FALSE, scale = FALSE)

Arguments

matrix.pval	a matrix of p-values as returned by function many.pval.
xi	a vector of values at which to compute the empirical distribution of the p-values.
type	character. Indicate the type of plot desired.
center	Logical. Should we center the data generated
scale	Logical. Should we center the data generated

Details

See Section 2.3 in Lafaye de Micheaux, P. and Tran, V. A. (2014).

Author(s)

P. Lafaye de Micheaux, V. A. Tran

References

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

See Also

See plot.pvalue, plot.discrepancy, plot.sizepower.

Examples

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.
# You can increase the values of M and N for better results.
matrix.pval <- many.pval(stat.indices=stind,law.index=1,
                        n=100,M=10,N=10,alter=alter,null.dist=1,
                        method="direct")
graph(matrix.pval)

Example output

Loading required package: parallel
Loading required package: Rcpp

PoweR documentation built on May 2, 2019, 2:09 p.m.