VarInverseGamma

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VarInverseGamma#

class liesel_ptm.VarInverseGamma(value, concentration, scale, name, bijector=<tfp.bijectors.Softplus 'softplus' batch_shape=[] forward_min_event_ndims=0 inverse_min_event_ndims=0 dtype_x=? dtype_y=?>)[source]#

Bases: Var

A variable with an inverse gamma prior.

Parameters:

  • value (float) – Initial value of the variable.

  • concentration (float | Var | Node) – Concentration parameter of the inverse gamma distribution. In some parameterizations, this parameter is called a.

  • scale (float | Var | Node) – Scale parameter of the inverse gamma distribution. In some parameterizations, this parameter is called b.

  • name (str) – Name of the variable.

  • bijector (Bijector | None) – A tensorflow bijector instance. If a bijector is supplied, the variable will be transformed using the bijector. This renders the variable itself weak, meaning that it is a deterministic function of the newly created transformed variable. The prior is transferred to this transformed variable and transformed according to the change-of-variables theorem. (default: <tfp.bijectors.Softplus 'softplus' batch_shape=[] forward_min_event_ndims=0 inverse_min_event_ndims=0 dtype_x=? dtype_y=?>)

Methods

predict

Returns posterior samples of this variable.

Attributes

transformed

The transformed variable (if any).
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