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qualityTools (version 1.55)

ppPlot: Probability Plots for various distributions

Description

ppPlot creates a Probability plot of the values in x including a line.

Usage

ppPlot(x, distribution,  confbounds = TRUE, alpha, probs, main, xlab, ylab, 
       xlim, ylim, border = "red", bounds.col = "black", bounds.lty = 1, 
       grid = TRUE, box = TRUE, stats = TRUE, start, ...)

Arguments

x
vector containing the sample for ppPlot.
distribution
character string specifying the distribution of x. The function ppPlot will support the following character strings for distribution:
  • beta
  • cauchy
  • chi-squared
confbounds
boolean value: TRUE if confidence bounds should be drawn (default value).
alpha
significance level for the confidence bounds, set on 0.05 by default.
probs
vector containing the percentages for the y axis. All the values need to be between 0 and 1 If probs is missing it will be calculated internally.
main
an overall title for the plot: see title.
xlab
a title for the x axis: title.
ylab
a title for the y axis: title.
xlim
vector giving the range of the x-axis.
ylim
vector giving the range of the y-axis.
border
numerical value or single character string giving the color of interpolation line. By default border is set to red.
bounds.col
numerical value or single character string giving the color of confidence bounds lines. By default bounds is set to black.
bounds.lty
numerical value giving the color of confidence bounds lines. By default bounds is set to 1.
grid
logical value, deciding whether a grid will be added to the current plot. By default grid is set to TRUE.
box
logical value, deciding whether a box is drawn to around the current plot. By default box is set to TRUE.
stats
logical value deciding whether ppPlot returns the values listed under value. By default stats is set to TRUE.
start
A named list giving the parameters to be fitted with initial values. Must be supplied for some distribution. (see Details)
...
further graphical parameters (see par).

Value

  • ppPlot returns a list containing the following: x - x coordinates y - y coordinates int - Intercept slope - slope

Details

Distribution fitting is deligated to function fitdistr of the R-package MASS. For computation of the confidence bounds the variance of the quantiles is estimated using the delta method, which implies estimation of observed Fisher Information matrix as well as the gradient of the CDF of the fitted distribution. Where possible, those values are replaced by their normal approximation.

See Also

qqPlot fitdistr in R-package MASS http://www.r-qualitytools.org/html/Analyze.html

Examples

Run this code
#set up the plotting window for 6 plots
par(mfrow = c(3,2))

#generate random data from weibull distribution
x = rweibull(20, 8, 2)

#Probability Plot for different distributions
ppPlot(x, "log-normal")
ppPlot(x, "normal")
ppPlot(x, "exponential", DB = TRUE)
ppPlot(x, "cauchy")
ppPlot(x, "weibull")
ppPlot(x, "logistic")

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