`altar.models.regression`

Submodules

Package Contents

Classes

Functions

class altar.models.regression.model

Bases: altar.protocol

The protocol that all AlTar models must implement

posterior(self, application): Sample my posterior distribution

initialize(self, application): Initialize the state of the model given a {problem} specification

initializeSample(self, step): Fill {step.theta} with an initial random sample from my prior distribution.

priorLikelihood(self, step): Fill {step.prior} with the likelihoods of the samples in {step.theta} in the prior distribution

dataLikelihood(self, step): Fill {step.data} with the likelihoods of the samples in {step.theta} given the available data. This is what is usually referred to as the “forward model”

posteriorLikelihood(self, step): Given the {step.prior} and {step.data} likelihoods, compute a generalized posterior using {step.beta} and deposit the result in {step.post}

likelihoods(self, step): Convenience function that computes all three likelihoods at once given the current {step} of the problem

verify(self, step, mask): Check whether the samples in {step.theta} are consistent with the model requirements and update the {mask}, a vector with zeroes for valid samples and non-zero for invalid ones

top(self, annealer): Notification that a β step is about to start

bottom(self, annealer): Notification that a β step just ended

forwardProblem(self, application, theta=None): Perform the forward modeling with given {theta}

classmethod pyre_default(cls, **kwds): Supply a default implementation

altar.models.regression.linear()