plotmix {bayess} R Documentation

## Graphical representation of a normal mixture log-likelihood

### Description

This function gives an image representation of the log-likelihood surface of a mixture (Chapter 6) of two normal densities with means \mu_1 and \mu_2 unknown. It first generates the random sample associated with the distribution.

### Usage

plotmix(mu1 = 2.5, mu2 = 0, p = 0.7, n = 500, plottin = TRUE, nl = 50)


### Arguments

 mu1 first mean mu2 second mean p weight of the first component n number of observations plottin boolean variable to plot the surface (or not) nl number of contours

### Details

In this case, the parameters are identifiable: \mu_1 and \mu_2 cannot be confused when p is not 0.5. Nonetheless, the log-likelihood surface in this figure often exhibits two modes, one being close to the true value of the parameters used to simulate the dataset and one corresponding to a reflected separation of the dataset into two homogeneous groups.

### Value

 sample  the simulated sample like  the discretised representation of the log-likelihood surface

resumix=plotmix()