pymc.MvStudentTRandomWalk

class pymc.MvStudentTRandomWalk(name, *args, **kwargs)

Multivariate Random Walk with StudentT innovations

Parameters

nu: int

degrees of freedom

mu: tensor_like of float

innovation drift

scale: tensor_like of float

pos def matrix, innovation covariance matrix

tau: tensor_like of float

pos def matrix, inverse covariance matrix

chol: tensor_like of float

Cholesky decomposition of covariance matrix

lowerbool, default=True

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

init_dist: distribution

Unnamed multivariate distribution of the initial value. Unnamed refers to distributions

created with the .dist() API.

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

MvStudentTRandomWalk.__init__(*args, **kwargs)
MvStudentTRandomWalk.dist(*args, **kwargs)
MvStudentTRandomWalk.get_dists(*, nu, mu[, ...])
MvStudentTRandomWalk.mro(/)	Return a type's method resolution order.
MvStudentTRandomWalk.register(subclass)	Register a virtual subclass of an ABC.