STAR (version 0.3-7)

qqDuration: Quantile-Quantile Plot For Fitted Duration Distributions

Description

Produces a QQ plot of empirical against theoretical quantiles of one of the following duration distributions: inverse Gaussian, log normal, log logistic, refractory exponential, gamma, weibull.

Usage

qqDuration(durationFit, CI = c(0.95, 0.99), type = "l", xlab, ylab, main, sub, ylim, dataLwd = 2, ablineCol = 2, ...)

Arguments

durationFit

a durationFit object, that is, a list returned by one of these functions: invgaussMLE, lnormMLE, llogisMLE, rexpMLE, gammaMLE, weibullMLE.

CI

a numeric vector with at most tow components, the confidence intervals to be drawn. If NULL, intervals are not drawn.

type, xlab, ylab, main, sub, ylim

see plot, default values are provided if arguments are missing.

dataLwd

non negative integer, the width of the line used to draw the data.

ablineCol

color of the diagonal.

...

additional arguments passed to plot.

Value

Nothing is returned, the function is used for its side effect, a plot is generated.

Details

If the data to which the model was fitted have censored events, the latter are not used to build the empirical quantiles.

See Also

compModels, invgaussMLE, lnormMLE, llogisMLE, rexpMLE, gammaMLE, weibullMLE

Examples

## Not run: 
# ## Simulate a sample with 100 events from an inverse Gaussian
# set.seed(1102006,"Mersenne-Twister")
# mu.true <- 0.075
# sigma2.true <- 3
# sampleSize <- 100
# sampIG <- rinvgauss(sampleSize,mu=mu.true,sigma2=sigma2.true)
# ## Fit it with an inverse Gaussian Model
# sampIGmleIG <- invgaussMLE(sampIG)
# ## draw the QQ plot on a log scale
# qqDuration(sampIGmleIG,log="xy")
# ## Fit it with a log normal Model
# sampIGmleLN <- lnormMLE(sampIG)
# ## draw the QQ plot on a log scale
# qqDuration(sampIGmleLN,log="xy")
# ## Fit it with a gamma Model
# sampIGmleGA <- gammaMLE(sampIG)
# ## draw the QQ plot on a log scale
# qqDuration(sampIGmleGA,log="xy")
# ## Fit it with a Weibull Model
# sampIGmleWB <- weibullMLE(sampIG)
# ## draw the QQ plot on a log scale
# qqDuration(sampIGmleWB,log="xy")
# ## Fit it with a refractory exponential Model
# sampIGmleRE <- rexpMLE(sampIG)
# ## draw the QQ plot on a log scale
# qqDuration(sampIGmleRE,log="xy")
# ## Fit it with a log logisitc Model
# sampIGmleLL <- llogisMLE(sampIG)
# ## draw the QQ plot on a log scale
# qqDuration(sampIGmleLL,log="xy")
# ## End(Not run)