condMom {bayesm} | R Documentation

## Computes Conditional Mean/Var of One Element of MVN given All Others

### Description

`condMom` compute moments of conditional distribution of ith element of normal given all others.

### Usage

    condMom(x, mu, sigi, i)

### Arguments

`x` | vector of values to condition on - ith element not used
`mu` | length(x) mean vector
`sigi` | length(x)-dim covariance matrix
`i` | conditional distribution of ith element

### Details

x ~ MVN(mu,Sigma).

`condMom` computes moments of x_i given x_{-i}.

### Value

a list containing:

`cmean` | cond mean
`cvar` | cond variance

### 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.
http://gsbwww.uchicago.edu/fac/peter.rossi/research/bsm.html

### Examples

    ##
    sig=matrix(c(1,.5,.5,.5,1,.5,.5,.5,1),ncol=3)
    sigi=chol2inv(chol(sig))
    mu=c(1,2,3)
    x=c(1,1,1)
    condMom(x,mu,sigi,2)

[Package bayesm version 2.0-8 Index]