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Multivariate Normal with Full Covariance¤

distreqx.distributions.MultivariateNormalFullCovariance ¤

Multivariate normal distribution on \(\mathbb{R}^k\).

The MultivariateNormalFullCovariance distribution is parameterized by a \(k\)-length location (mean) vector \(b\) and a covariance matrix \(C\) of size \(k \times k\) that must be positive definite and symmetric.

Note

This class makes no attempt to verify that the covariance matrix is positive definite or symmetric. The underlying Cholesky decomposition will simply fail if these conditions are not met.

__init__(loc: typing.Optional[Array] = None, covariance_matrix: typing.Optional[Array] = None) ¤

Initializes a MultivariateNormalFullCovariance distribution.

Arguments:

  • loc: Mean vector of the distribution of shape k. If not specified, it defaults to zeros.
  • covariance_matrix: The covariance matrix C. It must be a k x k symmetric positive definite matrix. If not specified, it defaults to the identity matrix.