pymc.MvStudentTRandomWalk#
- class pymc.MvStudentTRandomWalk(name, *args, **kwargs)[source]#
Multivariate Random Walk with StudentT innovations
- Parameters:
- nu
int degrees of freedom
- mutensor_like of
float innovation drift
- scaletensor_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.
- steps
int, optional Number of steps in Random Walk (steps > 0). Only needed if shape is not provided.
- nu
Notes
Only one of cov, tau or chol is required.
Methods
MvStudentTRandomWalk.dist(*args, **kwargs)