PoweR (version 1.1.4)

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

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)

Value

No return value. Displays a graph.

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

Author

P. Lafaye de Micheaux, V. A. Tran

Details

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

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)