display.pcurve: A Wrapper Function for Plotting P-Curves

In ddarmon/clp: R Package for Computing Confidence Functions to Accompany CLP

Description

A wrapper for plotting P-curves using confidence objects returned by *.conf() functions from clp.

Usage

display.pcurve(
  obj,
  conf.level = 0.95,
  xlim = NULL,
  xlab = NULL,
  log = "",
  col = "black",
  n.points = 2001
)

Arguments

obj	a list of confidence functions returned by a *.conf() function
conf.level	the confidence level for the confidence interval indicated on the P-curve
xlim	the horizontal limits for the plot. If NULL, taken as the larger of a conf.level confidence interval or a 1 - (1 - conf.level)/2 confidence interval.
xlab	the label for the horizontal axis
log	switch for plotting the horizontal ('x') or vertical ('x') or both ('xy') axes with a log-scaling
col	the color to plot the confidence curve
n.points	the number of points to plot for the confidence curve

Value

a plot of the P-curve from obj

References

Tore Schweder and Nils Lid Hjort. Confidence, likelihood, probability. Vol. 41. Cambridge University Press, 2016.

Examples

data(dietstudy)

x <- dietstudy$weightchange[dietstudy$diet == 'Low Carb']

out <- t_test.conf(x, plot = FALSE)

display.pcurve(out, conf.level = 0.999, xlab = 'Average Weight Loss in Low Carb Group (lbs)')

ddarmon/clp documentation built on Jan. 25, 2021, 6:22 p.m.