logpdf_lazy_matrix_gaussian

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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.