| QQplotGMM {AdaptGauss} | R Documentation |
Quantile Quantile plot of data against gaussian distribution mixture model with optional best-fit-line
QQplotGMM(Data,Means,SDs,Weights,IsLogDistribution,Line,
PlotSymbol,xug,xog,LineWidth,PointWidth, ylab,main, ...)
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 |
Line |
Optional, Default: TRUE=Regression Line is drawn |
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 |
ylab |
Optional, see |
main |
Optional, see |
... |
Note: xlab cannot be changed, other parameters see |
Only verified for a Gaussian Mixture Model, usage of IsLogDistribution for LogNormal Modes is experimental!
List with
x |
The x coordinates of the points that were plotted |
y |
The original data vector, i.e., the corresponding y coordinates |
Michael Thrun
Michael, J. R. (1983). The stabilized probability plot. Biometrika, 70(1), 11-17.
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))