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 `i`

th element of a multivariate normal given all others.

### Usage

`condMom(x, mu, sigi, i)`

### Arguments

`x` |
vector of values to condition on; |

`mu` |
mean vector with |

`sigi` |
inverse of covariance matrix; dimension |

`i` |
conditional distribution of |

### 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]