QQplotGMM: Quantile Quantile Plot of Data

Description

Quantile Quantile plot of data against gaussian distribution mixture model with optional best-fit-line

Usage

QQplotGMM(Data,Means,SDs,Weights,IsLogDistribution,Method,Line,
PlotSymbol,col,xug,xog,LineWidth,PointWidth,PositiveData,Type,NoQuantiles,
ylabel,main,lwd,pch,xlabel,...)

Value

List with

x: The x coordinates of the points that were plotted
y: The original data vector, i.e., the corresponding y coordinates

Arguments

Data: vector (1:N) of data points
Means: vector[1:L] of Means of Gaussians (of GMM),L == Number of Gaussians
SDs: vector of standard deviations, estimated Gaussian Kernels, has to be the same length as Means
Weights: vector of relative number of points in Gaussians (prior probabilities), has to be the same length as Means
IsLogDistribution: Optional, ==1 if distribution(i) is a LogNormal, default Zeros of Length L
Method: Optional, ==1 default. ==2 for robust calculation
Line: Optional, Default: TRUE=Regression Line is drawn
col: Character: color of regression line (only for Method = 2)
xug: Optional, lower limit of the interval [xug, xog], in which a line will be interpolated
xog: Optional, upper limit of the interval [xug, xog], in which a line will be interpolated
PlotSymbol: Optional, plot symbol. Default is 20.
LineWidth: Optional, width of regression line, if Line==TRUE
PointWidth: Optional, width of points
PositiveData: Optional, Boolean: If true only positive values of GMM sampling are used. Default FALSE
Type: Optional,Integer: number of method used for computing the quantiles, see quantile
NoQuantiles: Optional, Integer: Number of quantiles to compute (only for Method = 2)
ylabel: Optional, see plot
main: Optional, see plot
lwd: Optional, Integer: graphic parameter - line width option (only for Method = 2)
pch: Integer: graphic parameter for points (only for Method = 2)
xlabel: Optional, see plot
...: Note: xlab cannot be changed, other parameters see qqplot

Author

Michael Thrun

Details

Only verified for a Gaussian Mixture Model, usage of IsLogDistribution for LogNormal Modes is experimental!

References

Michael, J. R. (1983). The stabilized probability plot. Biometrika, 70(1), 11-17.

Examples

Run this code

data=c(rnorm(1000),rnorm(2000)+2,rnorm(1000)*2-1)
QQplotGMM(data,c(-1,0,2),c(2,1,1),c(0.25,0.25,0.5))

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