pymc.MvGaussianRandomWalk#
- class pymc.MvGaussianRandomWalk(*args, **kwargs)[source]#
Multivariate Random Walk with Normal innovations
- Parameters
- mu: tensor
innovation drift, defaults to 0.0
- cov: tensor
pos def matrix, innovation covariance matrix
- tau: tensor
pos def matrix, inverse covariance matrix
- chol: tensor
Cholesky decomposition of covariance matrix
- init: distribution
distribution for initial value (Defaults to Flat())
Notes
Only one of cov, tau or chol is required.
Methods
MvGaussianRandomWalk.__init__
([mu, cov, ...])MvGaussianRandomWalk.dist
(*args, **kwargs)Creates a tensor variable corresponding to the cls distribution.
Calculate log-probability of Multivariate Gaussian Random Walk distribution at specified value.
MvGaussianRandomWalk.random
(**kwargs)Attributes
rv_class
rv_op