From ad4ac5e12a649082f2e33230d2dc9184ea47d5d4 Mon Sep 17 00:00:00 2001
From: Pierre Santagostini <pierre.santagostini@agrocampus-ouest.fr>
Date: Thu, 4 Jul 2024 20:44:09 +0200
Subject: [PATCH] Small corrections
---
man/kldcauchy.Rd | 10 +++++-----
1 file changed, 5 insertions(+), 5 deletions(-)
diff --git a/man/kldcauchy.Rd b/man/kldcauchy.Rd
index d53f68f..95d2df4 100644
--- a/man/kldcauchy.Rd
+++ b/man/kldcauchy.Rd
@@ -23,9 +23,9 @@ Computes the Kullback-Leibler divergence between two random vectors distributed
according to multivariate Cauchy distributions (MCD) with zero location vector.
}
\details{
-Given \eqn{X_1}, a random vector of \eqn{R^p} distributed according to the MCD
+Given \eqn{X_1}, a random vector of \eqn{\mathbb{R}^p} distributed according to the MCD
with parameters \eqn{(0, \Sigma_1)}
-and \eqn{X_2}, a random vector of \eqn{R^p} distributed according to the MCD
+and \eqn{X_2}, a random vector of \eqn{\mathbb{R}^p} distributed according to the MCD
with parameters \eqn{(0, \Sigma_2)}.
Let \eqn{\lambda_1, \dots, \lambda_p} the eigenvalues of the square matrix \eqn{\Sigma_1 \Sigma_2^{-1}}
@@ -48,9 +48,9 @@ is given by:
}
where \eqn{F_D^{(p)}} is the Lauricella \eqn{D}-hypergeometric function defined for \eqn{p} variables:
-\deqn{ \displaystyle{ F_D^{(p)}\left(a; b_1, ..., b_p; g; x_1, ..., x_p\right) = \sum\limits_{m_1 \geq 0} ... \sum\limits_{m_p \geq 0}{ \frac{ (a)_{m_1+...+m_p}(b_1)_{m_1} ... (b_p)_{m_p} }{ (g)_{m_1+...+m_p} } \frac{x_1^{m_1}}{m_1!} ... \frac{x_p^{m_p}}{m_p!} } } }
-
-The computation of the partial derivative uses the \code{\link{pochhammer}} function.
+\deqn{ \displaystyle{ F_D^{(p)}\left(a; b_1, ..., b_p; g; x_1, ..., x_p\right) = \sum\limits_{m_1 \geq 0} ... \sum\limits_{m_p \geq 0}{ \frac{ (a)_{m_1+...+m_p}(b_1)_{m_1} ... (b_p)_{m_p} }{ (g)_{m_1+...+m_p} } \frac{x_1^{m_1}}{m_1!} ... \frac{x_p^{m_p}}{m_p!} } } }\if{html}{\out{
+<!-- The computation of the partial derivative uses the \code{\link{pochhammer}} function. -->
+}}
}
\examples{
\donttest{
--
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