pymc.GaussianRandomWalk#

class pymc.GaussianRandomWalk(*args, steps=None, **kwargs)[source]#

Random Walk with Normal innovations.

Parameters
mutensor_like of float, default 0

innovation drift

sigmatensor_like of float, default 1

sigma > 0, innovation standard deviation.

init_distDistribution
Unnamed univariate distribution of the initial value. Unnamed refers to distributions

created with the .dist() API.

Warning

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

stepsint, optional

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

Methods

GaussianRandomWalk.__init__(*args, **kwargs)

GaussianRandomWalk.dist([mu, sigma, ...])

Creates a tensor variable corresponding to the cls distribution.

GaussianRandomWalk.logp(mu, sigma, ...)

Calculate log-probability of Gaussian Random Walk distribution at specified value.

GaussianRandomWalk.moment(size, mu, sigma, ...)

Attributes

rv_class

rv_op