logpdf_lazy_matrix_gaussian


function logpdf_lazy_matrix_gaussian(X:Expression<Real[_,_]>, M:Expression<Real[_,_]>, U:Expression<LLT>, V:Expression<LLT>) -> Expression<Real>

Observe a matrix Gaussian distribution.

  • X: The variate.
  • M: Mean.
  • U: Among-row covariance.
  • V: Among-column covariance.

Returns: the log probability density.

function logpdf_lazy_matrix_gaussian(X:Expression<Real[_,_]>, M:Expression<Real[_,_]>, U:Expression<LLT>, σ2:Expression<Real[_]>) -> Expression<Real>

Observe a matrix Gaussian distribution with independent columns.

  • X: The variate.
  • M: Mean.
  • U: Among-row covariance.
  • σ2: Among-column variances.

Returns: the log probability density.

function logpdf_lazy_matrix_gaussian(X:Expression<Real[_,_]>, M:Expression<Real[_,_]>, V:Expression<LLT>) -> Expression<Real>

Observe a matrix Gaussian distribution with independent rows.

  • X: The variate.
  • M: Mean.
  • V: Among-column covariance.

Returns: the log probability density.

function logpdf_lazy_matrix_gaussian(X:Expression<Real[_,_]>, M:Expression<Real[_,_]>, σ2:Expression<Real[_]>) -> Expression<Real>

Observe a matrix Gaussian distribution with independent elements.

  • X: The variate.
  • M: Mean.
  • σ2: Among-column variances.

Returns: the log probability density.

function logpdf_lazy_matrix_gaussian(X:Expression<Real[_,_]>, M:Expression<Real[_,_]>, σ2:Expression<Real>) -> Expression<Real>

Observe a matrix Gaussian distribution with independent elements of identical variance.

  • X: The variate.
  • M: Mean.
  • σ2: Variance.

Returns: the log probability density.