plot.FDX: Plot Method for 'FDX' objects

In FDX: False Discovery Exceedance Controlling Multiple Testing Procedures

Plot Method for FDX objects

Description

Plots raw $p$-values of a FDX object and highlights rejected and non-rejected $p$-values. If present, the critical values are plotted, too.

Usage

## S3 method for class 'FDX'
plot(
  x,
  col = c(2, 4, 1),
  pch = c(20, 20, 17),
  lwd = rep(par()$lwd, 3),
  cex = rep(par()$cex, 3),
  type.crit = "b",
  legend = NULL,
  ...
)

Arguments

x	an object of class "FDX".
col	numeric or character vector of length 3 indicating the colors of the rejected $p$-values non-rejected $p$-values critical values (if present).
pch	numeric or character vector of length 3 indicating the point characters of the rejected $p$-values non-rejected $p$-values critical values (if present and type.crit is a plot type like 'p', 'b' etc.).
lwd	numeric vector of length 3 indicating the thickness of the points and lines; defaults to current par()$lwd setting for all components.
cex	numeric vector of length 3 indicating the size of point characters or lines of the rejected p-values accepted p-values critical values (if present). defaults to current par()$cex setting for all components.
type.crit	single character giving the type of plot desired for the critical values (e.g.: 'p', 'l' etc; see graphics::plot.default()).
legend	if NULL, no legend is plotted; otherwise expecting a character string like "topleft" etc. or a numeric vector of two elements indicating (x, y) coordinates.
...	further arguments to graphics::plot.default().

Details

If x contains results of a weighted approach, the Y-axis of the plot is derived from the weighted p-values. Otherwise, it is constituted by the raw ones.

Examples

X1 <- c(4, 2, 2, 14, 6, 9, 4, 0, 1)
X2 <- c(0, 0, 1, 3, 2, 1, 2, 2, 2)
N1 <- rep(148, 9)
N2 <- rep(132, 9)
Y1 <- N1 - X1
Y2 <- N2 - X2
df <- data.frame(X1, Y1, X2, Y2)
df

# Construction of the p-values and their supports with Fisher's exact test
library(DiscreteTests)  # for Fisher's exact test
test.results <- fisher_test_pv(df)
raw.pvalues <- test.results$get_pvalues()
pCDFlist <- test.results$get_pvalue_supports()

# DLR without critical values; using extracted p-values and supports
DLR.sd.fast <- DLR(raw.pvalues, pCDFlist)
# plot with default settings
plot(DLR.sd.fast)

# DLR (step-up) with critical values; using test results object
DLR.su.crit <- DLR(test.results, direction = "su", critical.values = TRUE)
# limited plot range
plot(DLR.su.crit, xlim = c(1, 5), ylim = c(0, 0.4))

# DPB without critical values; using test results object
DPB.fast <- DPB(test.results)
# limited plot range, custom colors, line widths and point symbols, top-left legend 
plot(DPB.fast, col = c(2, 4), pch = c(2, 3), lwd = c(2, 2), 
     legend = "topleft", xlim = c(1, 5), ylim = c(0, 0.4))

# DGR with critical values; using extracted p-values and supports
DGR.crit <- DGR(raw.pvalues, pCDFlist, critical.values = TRUE)
# additional customized plot parameters
plot(DGR.crit, col = c(2, 4, 1), pch = c(1, 1, 4), lwd = c(1, 1, 2), 
     type.crit = 'o', legend = c(1, 0.4), lty = 1, xlim = c(1, 5), 
     ylim = c(0, 0.4), cex = c(3, 3, 2))

FDX documentation built on April 4, 2025, 4:08 a.m.