mvF {shrinkem} | R Documentation |
The matrix F Distribution
Description
Density and random generation for the matrix variate F distribution with first degrees
of freedom df1
, second degrees of freedom df2
, and scale matrix B
.
Usage
dmvF(x, df1, df2, B, log = FALSE)
rmvF(n, df1, df2, B)
Arguments
x |
Positive definite matrix of quantities. |
df1 |
First degrees of freedom |
df2 |
Second degrees of freedom |
B |
Positive definite scale matrix |
log |
logical; if TRUE, density is given as log(p). |
n |
Number of draws |
Value
dmvF
returns the probability density of the matrix F distribution.
rmvF
returns a numeric array, say R
, of dimension p \times p \times n
, where each element
R[,,i]
is a positive definite matrix, a realization of the matrix F distribution.
References
Mulder and Pericchi (2018). The Matrix-F Prior for Estimating and Testing Covariance Matrices. Bayesian Analysis, 13(4), 1193-1214. <https://doi.org/10.1214/17-BA1092>
Examples
set.seed(20180222)
draws_F <- rmvF(n=1, df1=2, df2=4, B=diag(2))
dmvF(draws_F[,,1], df1=2, df2=4, B=diag(2))
[Package shrinkem version 0.2.0 Index]