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Plots Gaussian Mixture Model without Bayes decision boundaries, such that:
Black is the PDE of Data
Red is color of the GMM
Blue is the color of components of the mixture
vector (1:N) of data points
vector[1:L] of Means of Gaussians (of GMM),L == Number of Gaussians
vector of standard deviations, estimated Gaussian Kernels, has to be the same length as Means
vector of relative number of points in Gaussians (prior probabilities), has to be the same length as Means
Optional, ==1 if distribution(i) is a LogNormal, default vector of zeros of length 1:L
Optional,Color for line plot of all the single gaussians, default magenta
Optional,Color of line lot for the mixture default red
Optional,Color of line plot for the data, default black
Optional, If TRUE, single gaussians are shown, default FALSE
Optional,Default:TRUE with axis, see argument axis of plot
axis
plot
Optional, see plot
Optional: Precalculated Pareto Radius to use
other plot arguments like xlim = c(1,10)
PlotMixturesAndBoundaries
# NOT RUN { data=c(rnorm(1000),rnorm(2000)+2,rnorm(1000)*2-1) PlotMixtures(data,c(-1,0,2),c(2,1,1),c(0.25,0.25,0.5),SingleColor='blue',SingleGausses=TRUE) # }
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