sample_post_nor_jef_marg_Psi {BayesMultMeta} | R Documentation |
Metropolis-Hastings algorithm for the normal distribution and the Jeffreys
prior, where
is generated from the marginal posterior.
Description
This function implements Metropolis-Hastings algorithm for drawing samples
from the posterior distribution of and
under the assumption of the normal distribution when the Jeffreys prior is
employed. At each step, the algorithm starts with generating a draw from the
marginal distribution of
.
Usage
sample_post_nor_jef_marg_Psi(X, U, Np)
Arguments
X |
A |
U |
A |
Np |
Length of the generated Markov chain. |
Value
List with the generated samples from the joint posterior distribution
of and
, where the values of
are presented by using the vec operator.
[Package BayesMultMeta version 0.1.1 Index]