gluonts.mx.distribution.inflated_beta module#
- class gluonts.mx.distribution.inflated_beta.OneInflatedBeta(alpha: Union[NDArray, Symbol], beta: Union[NDArray, Symbol], one_probability: Union[NDArray, Symbol])[source]#
Bases:
ZeroAndOneInflatedBeta
One Inflated Beta distribution as in Raydonal Ospina, Silvia L.P. Ferrari: Inflated Beta Distributions.
- Parameters:
alpha – Tensor containing the alpha shape parameters, of shape (*batch_shape, *event_shape).
beta – Tensor containing the beta shape parameters, of shape (*batch_shape, *event_shape).
one_probability – Tensor containing the probability of ones, of shape (*batch_shape, *event_shape).
F –
- arg_names: Tuple#
- is_reparameterizable = False#
- class gluonts.mx.distribution.inflated_beta.OneInflatedBetaOutput[source]#
Bases:
ZeroInflatedBetaOutput
- args_dim: Dict[str, int] = {'alpha': 1, 'beta': 1, 'one_probability': 1}#
- distr_cls#
alias of
OneInflatedBeta
- classmethod domain_map(F, alpha, beta, one_probability)[source]#
Maps raw tensors to valid arguments for constructing a ZeroInflatedBeta distribution.
- Parameters:
F –
alpha – Tensor of shape (*batch_shape, 1)
beta – Tensor of shape (*batch_shape, 1)
zero_probability – Tensor of shape (*batch_shape, 1)
- Returns:
Three squeezed tensors, of shape (*batch_shape): First two have entries mapped to the positive orthant, last is mapped to (0,1)
- Return type:
Tuple[Tensor, Tensor, Tensor]
- class gluonts.mx.distribution.inflated_beta.ZeroAndOneInflatedBeta(alpha: Union[NDArray, Symbol], beta: Union[NDArray, Symbol], zero_probability: Union[NDArray, Symbol], one_probability: Union[NDArray, Symbol])[source]#
Bases:
MixtureDistribution
Zero And One Inflated Beta distribution as in Raydonal Ospina, Silvia L.P. Ferrari: Inflated Beta Distributions
- Parameters:
alpha – Tensor containing the alpha shape parameters, of shape (*batch_shape, *event_shape).
beta – Tensor containing the beta shape parameters, of shape (*batch_shape, *event_shape).
zero_probability – Tensor containing the probability of zeros, of shape (*batch_shape, *event_shape).
one_probability – Tensor containing the probability of ones, of shape (*batch_shape, *event_shape).
F –
- arg_names: Tuple#
- is_reparameterizable = False#
- log_prob(x: Union[NDArray, Symbol]) Union[NDArray, Symbol] [source]#
Compute the log-density of the distribution at x.
- Parameters:
x – Tensor of shape (*batch_shape, *event_shape).
- Returns:
Tensor of shape batch_shape containing the log-density of the distribution for each event in x.
- Return type:
Tensor
- class gluonts.mx.distribution.inflated_beta.ZeroAndOneInflatedBetaOutput[source]#
Bases:
DistributionOutput
- args_dim: Dict[str, int] = {'alpha': 1, 'beta': 1, 'one_probability': 1, 'zero_probability': 1}#
- distr_cls#
alias of
ZeroAndOneInflatedBeta
- classmethod domain_map(F, alpha, beta, zero_probability, one_probability)[source]#
Maps raw tensors to valid arguments for constructing a ZeroAndOneInflatedBeta distribution.
- Parameters:
F –
alpha – Tensor of shape (*batch_shape, 1)
beta – Tensor of shape (*batch_shape, 1)
zero_probability – Tensor of shape (*batch_shape, 1)
- Returns:
Four squeezed tensors, of shape (*batch_shape): First two have entries mapped to the positive orthant, zero_probability is mapped to (0, 1), one_probability is mapped to (0, 1-zero_probability)
- Return type:
Tuple[Tensor, Tensor, Tensor, Tensor]
- property event_shape: Tuple#
Shape of each individual event contemplated by the distributions that this object constructs.
- property value_in_support: float#
A float that will have a valid numeric value when computing the log- loss of the corresponding distribution; by default 0.0.
This value will be used when padding data series.
- class gluonts.mx.distribution.inflated_beta.ZeroInflatedBeta(alpha: Union[NDArray, Symbol], beta: Union[NDArray, Symbol], zero_probability: Union[NDArray, Symbol])[source]#
Bases:
ZeroAndOneInflatedBeta
Zero Inflated Beta distribution as in Raydonal Ospina, Silvia L.P. Ferrari: Inflated Beta Distributions.
- Parameters:
alpha – Tensor containing the alpha shape parameters, of shape (*batch_shape, *event_shape).
beta – Tensor containing the beta shape parameters, of shape (*batch_shape, *event_shape).
zero_probability – Tensor containing the probability of zeros, of shape (*batch_shape, *event_shape).
F –
- arg_names: Tuple#
- is_reparameterizable = False#
- class gluonts.mx.distribution.inflated_beta.ZeroInflatedBetaOutput[source]#
Bases:
ZeroAndOneInflatedBetaOutput
- args_dim: Dict[str, int] = {'alpha': 1, 'beta': 1, 'zero_probability': 1}#
- distr_cls#
alias of
ZeroInflatedBeta
- classmethod domain_map(F, alpha, beta, zero_probability)[source]#
Maps raw tensors to valid arguments for constructing a ZeroInflatedBeta distribution.
- Parameters:
F –
alpha – Tensor of shape (*batch_shape, 1)
beta – Tensor of shape (*batch_shape, 1)
zero_probability – Tensor of shape (*batch_shape, 1)
- Returns:
Three squeezed tensors, of shape (*batch_shape): First two have entries mapped to the positive orthant, last is mapped to (0,1)
- Return type:
Tuple[Tensor, Tensor, Tensor]