| rejection.path | R Documentation | 
FDX objects)Displays the number of rejections of the raw p-values in a FDX
object in dependence of the exceedance probability zeta.
rejection.path(
  x,
  xlim = NULL,
  ylim = NULL,
  main = NULL,
  xlab = expression(zeta),
  ylab = "Number of Rejections",
  verticals = FALSE,
  pch = 19,
  ref.show = FALSE,
  ref.col = "gray",
  ref.lty = 2,
  ref.lwd = 2,
  ...
)
| x | object of class " | 
| xlim | x axis limits of the plot. If  | 
| ylim | the y limits of the plot. If  | 
| main | main title. If  | 
| xlab,ylab | labels for x and y axis. | 
| verticals | logical; if  | 
| pch | jump point character. | 
| ref.show | logical; if  | 
| ref.col | color of the reference line. | 
| ref.lty,ref.lwd | line type and thickness for the reference line. | 
| ... | further arguments to  | 
Invisibly returns a stepfun object that computes the number of
rejections in dependence on the exceedance probability zeta.
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 <- DLR(raw.pvalues, pCDFlist)
# plot number of rejections dependent on the exceedance probability zeta
rejection.path(DLR, xlim = c(0, 1), ref.show = TRUE, ref.col = "green", ref.lty = 4)
# None-adaptive DLR without critical values; using test results object
NDLR <- NDLR(test.results)
# add plot for non-adaptive procedure (in red)
rejection.path(NDLR, col = "red", add = TRUE)
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