qqPlot: Quantile-Quantile Plots for various distributions

In qualityTools: Statistical Methods for Quality Science

Description

qqPlot creates a QQ plot of the values in x including a line which passes through the first and third quartiles.

Usage

qqPlot(x, y, confbounds = TRUE, alpha, main, xlab, ylab, xlim, ylim, 
       border = "red", bounds.col = "black", bounds.lty = 1, start, ...)

Arguments

x	the sample for qqPlot
y	character string specifying the distribution of x. The function qqPlot will support the following character strings for y: “beta” “cauchy” “chi-squared” “exponential” “f” “gamma” “geometric” “log-normal” “lognormal” “logistic” “negative binomial” “normal” “Poisson” “t” “weibull” By default distribution is set to “normal”.
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.
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’.
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).

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.

Value

a list containing the x and y quantiles

x	sample quantiles
y	theoretical quantiles

Note

For an example in context which shows the usage of the function qqPlot() please read the vignette for the package qualityTools at http://www.r-qualitytools.org/html/Analyze.html.

Author(s)

Thomas Roth [e-mail]

See Also

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

Examples

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

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

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

Example output

Loading required package: Rsolnp
Loading required package: MASS

Attaching package: 'qualityTools'

The following object is masked from 'package:stats':

    sigma

Warning messages:
1: In densfun(x, parm[1], parm[2], ...) : NaNs produced
2: In densfun(x, parm[1], parm[2], ...) : NaNs produced
3: In densfun(x, parm[1], parm[2], ...) : NaNs produced
Warning messages:
1: In densfun(x, parm[1], parm[2], ...) : NaNs produced
2: In densfun(x, parm[1], parm[2], ...) : NaNs produced
3: In densfun(x, parm[1], parm[2], ...) : NaNs produced
4: In densfun(x, parm[1], parm[2], ...) : NaNs produced
5: In densfun(x, parm[1], parm[2], ...) : NaNs produced
6: In densfun(x, parm[1], parm[2], ...) : NaNs produced

qualityTools documentation built on May 2, 2019, 10:21 a.m.