GMMplot_ggplot2: Plots the Gaussian Mixture Model (GMM) withing ggplot2

In Mthrun/AdaptGauss: Gaussian Mixture Models (GMM)

Plots the Gaussian Mixture Model (GMM) withing ggplot2

Description

PlotMixtures and PlotMixturesAndBoundaries for ggplot2

Usage

GMMplot_ggplot2(Data, Means, SDs, Weights,

BayesBoundaries, SingleGausses = TRUE, Hist = FALSE)

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
BayesBoundaries	Optional, x values for baye boundaries, if missing 'BayesDecisionBoundaries' is called
SingleGausses	Optional, SingleGausses=T than components of the mixture in blue will be shown.
Hist	Optional, geom_histogram overlayed

Value

ggplot2 object

Note

MT standardized code for CRAN and added dec boundaries and doku

Author(s)

Joern Loetsch, Michael Thrun (ctb)

See Also

PlotMixturesAndBoundaries, PlotMixtures, BayesDecisionBoundaries

Examples

data=c(rnorm(1000),rnorm(2000)+2,rnorm(1000)*2-1)

GMMplot_ggplot2(data,c(-1,0,2),c(2,1,1),c(0.25,0.25,0.5),SingleGausses=TRUE)

Mthrun/AdaptGauss documentation built on July 31, 2023, 11:17 p.m.