Conditioned#
- class tinygp.means.Conditioned(X: tinygp.helpers.JAXArray, alpha: tinygp.helpers.JAXArray, kernel: Kernel, include_mean: bool, mean_function: Optional[Mean] = None)[source]#
Bases:
object
The mean of a process conditioned on observed data
- Parameters:
X – The coordinates of the data. alpha: The value \(L^-1\,y\) where L
the (is scale_tril and y is) – observed data.
scale_tril – The lower Cholesky factor of the base process’ kernel matrix.
kernel – The predictive kerenl; this will generally be the kernel from the kernel used by the original process.
include_mean – If
True
, the predicted values will include the mean function evaluated atX_test
.mean_function – The mean function of the base process. Used only if
include_mean
isTrue
.