GMMplot_ggplot2 {AdaptGauss} | R Documentation |

## 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)
```

[Package

*AdaptGauss*version 1.6 Index]