pymc.MvGaussianRandomWalk#

class pymc.MvGaussianRandomWalk(name, *args, **kwargs)[source]#

Random Walk with Multivariate Normal innovations

Parameters:
mutensor_like of float

innovation drift

covtensor_like of float

pos def matrix, innovation covariance matrix

tautensor_like of float

pos def matrix, inverse covariance matrix

choltensor_like of float

Cholesky decomposition of covariance matrix

lowerbool, default=True

Whether the cholesky fatcor is given as a lower triangular matrix.

init_distunnamed_distribution

Unnamed multivariate distribution of the initial value.

Warning

init_dist will be cloned, rendering them independent of the ones passed as input.

stepsint, optional

Number of steps in Random Walk (steps > 0). Only needed if shape is not provided.

Notes

Only one of cov, tau or chol is required.

Methods

MvGaussianRandomWalk.dist(*args, **kwargs)