pymc.gp.TP.prior#
- TP.prior(name, X, reparameterize=True, jitter=1e-06, **kwargs)[source]#
Return the TP prior distribution evaluated over the input locations X.
This is the prior probability over the space of functions described by its mean and covariance function.
- Parameters:
- name
str
Name of the random variable
- Xarray_like
Function input values. If one-dimensional, must be a column vector with shape (n, 1).
- reparameterizebool, default
True
Reparameterize the distribution by rotating the random variable by the Cholesky factor of the covariance matrix.
- 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