22.6 Multivariate Student-t distribution
22.6.1 Probability density function
If \(K \in \mathbb{N}\), \(\nu \in \mathbb{R}^+\), \(\mu \in \mathbb{R}^K\), and \(\Sigma \in \mathbb{R}^{K \times K}\) is symmetric and positive definite, then for \(y \in \mathbb{R}^K\), \[ \begin{array}{l} \text{MultiStudentT}(y\,|\,\nu,\,\mu,\,\Sigma) \\ = \frac{1}{\pi^{K/2}} \ \frac{1}{\nu^{K/2}} \ \frac{\Gamma\!\left((\nu + K)/2\right)} {\Gamma(\nu/2)} \ \frac{1}{\sqrt{\left| \Sigma \right|}} \ \left( 1 + \frac{1}{\nu} \, \left(y - \mu\right)^{\top} \, \Sigma^{-1} \, \left(y - \mu\right) \right)^{-(\nu + K)/2} \! . \end{array} \]
22.6.2 Sampling statement
y ~ multi_student_t(nu, mu, Sigma)
Increment target log probability density with multi_student_t_lupdf(y | nu, mu, Sigma).
22.6.3 Stan functions
real multi_student_t_lpdf(vectors y | real nu, vectors mu, matrix Sigma)
The log of the multivariate Student-\(t\) density of vector(s) y given
degrees of freedom nu, location vector(s) mu, and scale matrix Sigma
real multi_student_t_lupdf(vectors y | real nu, vectors mu, matrix Sigma)
The log of the multivariate Student-\(t\) density of vector(s) y given
degrees of freedom nu, location vector(s) mu, and scale matrix Sigma
dropping constant additive terms
real multi_student_t_lpdf(vectors y | real nu, row_vectors mu, matrix Sigma)
The log of the multivariate Student-\(t\) density of vector(s) y given
degrees of freedom nu, location row vector(s) mu, and scale matrix
Sigma
real multi_student_t_lupdf(vectors y | real nu, row_vectors mu, matrix Sigma)
The log of the multivariate Student-\(t\) density of vector(s) y given
degrees of freedom nu, location row vector(s) mu, and scale matrix
Sigma dropping constant additive terms
real multi_student_t_lpdf(row_vectors y | real nu, vectors mu, matrix Sigma)
The log of the multivariate Student-\(t\) density of row vector(s) y
given degrees of freedom nu, location vector(s) mu, and scale matrix
Sigma
real multi_student_t_lupdf(row_vectors y | real nu, vectors mu, matrix Sigma)
The log of the multivariate Student-\(t\) density of row vector(s) y
given degrees of freedom nu, location vector(s) mu, and scale matrix
Sigma dropping constant additive terms
real multi_student_t_lpdf(row_vectors y | real nu, row_vectors mu, matrix Sigma)
The log of the multivariate Student-\(t\) density of row vector(s) y
given degrees of freedom nu, location row vector(s) mu, and scale
matrix Sigma
real multi_student_t_lupdf(row_vectors y | real nu, row_vectors mu, matrix Sigma)
The log of the multivariate Student-\(t\) density of row vector(s) y
given degrees of freedom nu, location row vector(s) mu, and scale
matrix Sigma dropping constant additive terms
vector multi_student_t_rng(real nu, vector mu, matrix Sigma)
Generate a multivariate Student-\(t\) variate with degrees of freedom
nu, location mu, and scale matrix Sigma; may only be used in transformed data
and generated quantities blocks
vector multi_student_t_rng(real nu, row_vector mu, matrix Sigma)
Generate a multivariate Student-\(t\) variate with degrees of freedom
nu, location mu, and scale matrix Sigma; may only be used in transfomed data
and generated quantities blocks
vectors multi_student_t_rng(real nu, vectors mu, matrix Sigma)
Generate an array of multivariate Student-\(t\) variates with degrees of
freedom nu, locations mu, and scale matrix Sigma; may only be used in
transformed data and generated quantities blocks
vectors multi_student_t_rng(real nu, row_vectors mu, matrix Sigma)
Generate an array of multivariate Student-\(t\) variates with degrees of
freedom nu, locations mu, and scale matrix Sigma; may only be used in
transformed data andgenerated quantities blocks