mixDenBi {bayesm} | R Documentation

## Compute Bivariate Marginal Density for a Normal Mixture

### Description

`mixDenBi` computes the implied bivariate marginal density from a mixture of normals with specified mixture probabilities and component parameters.

### Usage

    mixDenBi(i, j, xi, xj, pvec, comps)

### Arguments

`i` | index of first variable
`j` | index of second variable
`xi` | grid of values of first variable
`xj` | grid of values of second variable
`pvec` | normal mixture probabilities
`comps` | list of lists of components

### Details

length(comps) is the number of mixture components. comps[[j]] is a list of parameters of the jth component. comps[[j]]$mu is mean vector; comps[[j]]$rooti is the UL decomp of Sigma^{-1}.

### Value

an array (length(xi)=length(xj) x 2) with density value

### Warning

This routine is a utility routine that does not check the input arguments for proper dimensions and type.

### Author(s)

Peter Rossi, Graduate School of Business, University of Chicago Peter.Rossi@ChicagoGsb.edu.

### References

For further discussion, see Bayesian Statistics and Marketing by Rossi, Allenby and McCulloch, Chapter 3.
http://gsbwww.uchicago.edu/fac/peter.rossi/research/bsm.html

### See Also

`rnmixGibbs`, `mixDen`

### Examples

    ## Not run:
    ##
    ##  see examples in rnmixGibbs documentation
    ##
    ## End(Not run)

[Package bayesm version 2.0-8 Index]