condMom {bayesm} R Documentation

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

### Description

condMom compute moments of conditional distribution of the ith element of a multivariate normal given all others.

### Usage

condMom(x, mu, sigi, i)

### Arguments

 x vector of values to condition on; ith element not used mu mean vector with length(x) = n sigi inverse of covariance matrix; dimension n x n i conditional distribution of ith element

### Details

x \sim MVN(mu, sigi^{-1}).

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

### Value

A list containing:

 cmean conditional mean cvar conditional variance

### Warning

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

### Author(s)

Peter Rossi, Anderson School, UCLA, perossichi@gmail.com.

### References

For further discussion, see Bayesian Statistics and Marketing by Rossi, Allenby, and McCulloch.

### Examples

sig  = matrix(c(1, 0.5, 0.5, 0.5, 1, 0.5, 0.5, 0.5, 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 3.1-6 Index]