mvnmvnp {Bolstad} | R Documentation |
Evaluates posterior density for mu, the mean of a MVN distribution, with a MVN prior on mu
mvnmvnp(y, m0 = 0, V0 = 1, Sigma = NULL, ...)
y |
a vector of observations from a MVN distribution with unknown mean and known variance-covariance. |
m0 |
the mean vector of the MVN prior, or a scalar constant so that the prior
vector of length k with the same element repeated k times, e.g. |
V0 |
the variance-covariance matrix of the MVN prior, or the diagonal of the variance-covariance matrix of the MVN prior, or a scalar constant, say n0, so the prior is n0 * I where I is the k by k identity matrix. |
Sigma |
the known variance covariance matrix of the data. If this value is NULL, which it is by default, then the sample covariance is used. NOTE: if this is the case then the cdf and quantile functions should really be multivariate t, but they are not - in which case the results are only (approximately) valid for large samples. |
... |
any other values to be passed to Bolstad.control |
A list will be returned with the following components:
mean |
the posterior mean of the MVN posterior distribution |
var |
the posterior variance-covariance matrix of the MVN posterior distribution |
cdf |
a function that will evaluation the posterior cdf at a given point. This function calls |
quantile |
a function that will find quantiles from the posterior given input probabilities. This function calls |