gluonts.torch.distributions.studentT module

class gluonts.torch.distributions.studentT.StudentT(df: Union[float, torch.Tensor], loc: Union[float, torch.Tensor] = 0.0, scale: Union[float, torch.Tensor] = 1.0, validate_args=None)

Bases: torch.distributions.studentT.StudentT

Student’s t-distribution parametrized by degree of freedom df, mean loc and scale scale.

Based on torch.distributions.StudentT, with added cdf and icdf methods.

cdf(value: torch.Tensor) → torch.Tensor

Returns the cumulative density/mass function evaluated at value.

Parameters

value (Tensor) –

icdf(value: torch.Tensor) → torch.Tensor

Returns the inverse cumulative density/mass function evaluated at value.

Parameters

value (Tensor) –

property scipy_student_t

class gluonts.torch.distributions.studentT.StudentTOutput(beta: float = 0.0)

Bases: gluonts.torch.distributions.distribution_output.DistributionOutput

args_dim: Dict[str, int] = {'df': 1, 'loc': 1, 'scale': 1}

distr_cls

alias of gluonts.torch.distributions.studentT.StudentT

classmethod domain_map(df: torch.Tensor, loc: torch.Tensor, scale: torch.Tensor)

Converts arguments to the right shape and domain.

The domain depends on the type of distribution, while the correct shape is obtained by reshaping the trailing axis in such a way that the returned tensors define a distribution of the right event_shape.

property event_shape: Tuple

Shape of each individual event compatible with the output object.

in_features: int