Expand source code

import numpy as np

from ..model import Model
from ..samplers.sampler import Sampler
from ..sigma import Sigma


class SigmaSampler(Sampler):

    def step(self, model: Model, sigma: Sigma) -> float:
        sample_value = self.sample(model, sigma)
        sigma.set_value(sample_value)
        return sample_value

    @staticmethod
    def sample(model: Model, sigma: Sigma) -> float:
        posterior_alpha = sigma.alpha + (model.data.X.n_obsv / 2.)
        posterior_beta = sigma.beta + (0.5 * (np.sum(np.square(model.residuals()))))
        draw = np.power(np.random.gamma(posterior_alpha, 1./posterior_beta), -0.5)
        return draw

Classes

class SigmaSampler

Helper class that provides a standard way to create an ABC using inheritance.

Expand source code

class SigmaSampler(Sampler):

    def step(self, model: Model, sigma: Sigma) -> float:
        sample_value = self.sample(model, sigma)
        sigma.set_value(sample_value)
        return sample_value

    @staticmethod
    def sample(model: Model, sigma: Sigma) -> float:
        posterior_alpha = sigma.alpha + (model.data.X.n_obsv / 2.)
        posterior_beta = sigma.beta + (0.5 * (np.sum(np.square(model.residuals()))))
        draw = np.power(np.random.gamma(posterior_alpha, 1./posterior_beta), -0.5)
        return draw

Ancestors

Sampler
abc.ABC

Static methods

def sample(model: Model, sigma: Sigma) ‑> float

Expand source code

@staticmethod
def sample(model: Model, sigma: Sigma) -> float:
    posterior_alpha = sigma.alpha + (model.data.X.n_obsv / 2.)
    posterior_beta = sigma.beta + (0.5 * (np.sum(np.square(model.residuals()))))
    draw = np.power(np.random.gamma(posterior_alpha, 1./posterior_beta), -0.5)
    return draw

Methods

def step(self, model: Model, sigma: Sigma) ‑> float

Expand source code

def step(self, model: Model, sigma: Sigma) -> float:
    sample_value = self.sample(model, sigma)
    sigma.set_value(sample_value)
    return sample_value