pymc.gp.TP.conditional#
- TP.conditional(name, Xnew, jitter=1e-06, **kwargs)[source]#
Return the conditional distribution evaluated over new input locations Xnew.
Given a set of function values f that the TP prior was over, the conditional distribution over a set of new points, f_* is
- Parameters:
- name
str
Name of the random variable
- Xnewarray_like
Function input values. If one-dimensional, must be a column vector with shape (n, 1).
- jitter
float
, default 1e-6 A small correction added to the diagonal of positive semi-definite covariance matrices to ensure numerical stability.
- **kwargs
Extra keyword arguments that are passed to
MvStudentT
distribution constructor.
- name