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25.3 Multivariate normal distribution, Cholesky parameterization

25.3.1 Probability density function

If $K \in \mathbb{N}$, $\mu \in \mathbb{R}^K$, and $L \in \mathbb{R}^{K \times K}$ is lower triangular and such that $LL^{\top}$ is positive definite, then for $y \in \mathbb{R}^K$, $$\text{MultiNormalCholesky}(y|\mu,L) = \text{MultiNormal}(y|\mu,LL^{\top}).$$ If $L$ is lower triangular and $LL^{top}$ is a $K \times K$ positive definite matrix, then $L_{k,k}$ must be strictly positive for $k \in 1{:}K$. If an $L$ is provided that is not the Cholesky factor of a positive-definite matrix, the probability functions will raise errors.

25.3.2 Sampling statement

y ~ multi_normal_cholesky(mu, L)

Increment target log probability density with multi_normal_cholesky_lupdf(y | mu, L).
Available since 2.0

25.3.3 Stan functions

real multi_normal_cholesky_lpdf(vectors y | vectors mu, matrix L)
The log of the multivariate normal density of vector(s) y given location vector(s) mu and lower-triangular Cholesky factor of the covariance matrix L
Available since 2.18

real multi_normal_cholesky_lupdf(vectors y | vectors mu, matrix L)
The log of the multivariate normal density of vector(s) y given location vector(s) mu and lower-triangular Cholesky factor of the covariance matrix L dropping constant additive terms
Available since 2.25

real multi_normal_cholesky_lpdf(vectors y | row_vectors mu, matrix L)
The log of the multivariate normal density of vector(s) y given location row vector(s) mu and lower-triangular Cholesky factor of the covariance matrix L
Available since 2.18

real multi_normal_cholesky_lupdf(vectors y | row_vectors mu, matrix L)
The log of the multivariate normal density of vector(s) y given location row vector(s) mu and lower-triangular Cholesky factor of the covariance matrix L dropping constant additive terms
Available since 2.25

real multi_normal_cholesky_lpdf(row_vectors y | vectors mu, matrix L)
The log of the multivariate normal density of row vector(s) y given location vector(s) mu and lower-triangular Cholesky factor of the covariance matrix L
Available since 2.18

real multi_normal_cholesky_lupdf(row_vectors y | vectors mu, matrix L)
The log of the multivariate normal density of row vector(s) y given location vector(s) mu and lower-triangular Cholesky factor of the covariance matrix L dropping constant additive terms
Available since 2.25

real multi_normal_cholesky_lpdf(row_vectors y | row_vectors mu, matrix L)
The log of the multivariate normal density of row vector(s) y given location row vector(s) mu and lower-triangular Cholesky factor of the covariance matrix L
Available since 2.18

real multi_normal_cholesky_lupdf(row_vectors y | row_vectors mu, matrix L)
The log of the multivariate normal density of row vector(s) y given location row vector(s) mu and lower-triangular Cholesky factor of the covariance matrix L dropping constant additive terms
Available since 2.25

vector multi_normal_cholesky_rng(vector mu, matrix L)
Generate a multivariate normal variate with location mu and lower-triangular Cholesky factor of the covariance matrix L; may only be used in transformed data and generated quantities blocks
Available since 2.3

vector multi_normal_cholesky_rng(row_vector mu, matrix L)
Generate a multivariate normal variate with location mu and lower-triangular Cholesky factor of the covariance matrix L; may only be used in transformed data and generated quantities blocks
Available since 2.18

vectors multi_normal_cholesky_rng(vectors mu, matrix L)
Generate an array of multivariate normal variates with locations mu and lower-triangular Cholesky factor of the covariance matrix L; may only be used in transformed data and generated quantities blocks
Available since 2.18

vectors multi_normal_cholesky_rng(row_vectors mu, matrix L)
Generate an array of multivariate normal variates with locations mu and lower-triangular Cholesky factor of the covariance matrix L; may only be used in transformed data and generated quantities blocks
Available since 2.18