diwishart_inverse: Inverted Wishart density from the inverse (faster).

In lgaborini/bayessource: Bayesian approach to evaluate whether two datasets come from the same population

Description

Computes the pdf p_X(x) by knowing x^(-1)

Usage

diwishart_inverse(X_inv, df, Sigma, logd = FALSE, is_chol = FALSE)

Arguments

X_inv	inverse of X (the data)
df	degrees of freedom of the Inverted Wishart
Sigma	scale matrix of the Inverted Wishart
logd	if TRUE, return the log-density
is_chol	if TRUE, Sigma and X_inv are the upper Cholesky factors of Sigma and X_inv

Details

Computes the density of an Inverted Wishart (df, Sigma) in x, by supplying (x^(-1), df, Sigma) rather than (x, df, Sigma). Avoids a matrix inversion.

Inverted Wishart parametrization (Press)

Uses \insertCitePress2012Appliedbayessource parametrization.

X ~ IW(v, S)

with S is a p x p matrix, v > 2p (the degrees of freedom).

Then:

E[X] = S/(n - 2(p + 1))

References

\insertAllCited

See Also

diwishart, dwishart

Other C++ functions: chol2inv(), dmvnorm(), inv_Cholesky_from_Cholesky(), inv_sympd_tol(), inv_triangular(), isCholeskyOn(), ldet_from_Cholesky(), logCummeanExp(), logCumsumExp(), logSumExpMean(), logSumExp(), marginalLikelihood_internal(), rmvnorm(), rwish()

Other statistical functions: diwishart_inverse_R(), diwishart(), dmvnorm(), dwishart(), riwish_Press(), rmvnorm(), rwish()

Other Wishart functions: diwishart_inverse_R(), diwishart(), dwishart(), get_minimum_nw_IW(), riwish_Press(), rwish()

lgaborini/bayessource documentation built on Nov. 9, 2021, 2:10 p.m.