rnorm.cg {lcd}R Documentation

Random normal sample from a chain graph

Description

Generates a desired number of normal random samples from a given chain graph structure and a given block-recursive regression system compatible with the chain graph.

Usage

rnorm.cg(n, amat, Bstar)

Arguments

n the intended sample size, should be at least 1.
amat the adjacency matrix of a chain graph.
Bstar the matrix representation of the block-recursive regression structure, e.g., the one returned by get.normal.dist.

Details

The function uses a mean 0 block-recursive regression model (See Wermuth (1992)), which is recorded in Bstar and normal random samples are generated from the specified block-recursive regression model.

Value

An n by p matrix with each row corresponding to a random sample.

Author(s)

Zongming Ma and Xiangrui Meng

References

Wermuth, N. (1992). Block-recursive regression equations (with discussions). Revista Brasileira de Probabilidade e Estatistica, 6, 1-56.


[Package lcd version 0.7-2 Index]