easypheno.model._bayesfromR

Module Contents

Classes

Bayes_R

Implementation of a class for Bayesian alphabet.

class easypheno.model._bayesfromR.Bayes_R(task, model_name, encoding=None, n_iter=6000, burn_in=1000)

Bases: easypheno.model._param_free_base_model.ParamFreeBaseModel

Implementation of a class for Bayesian alphabet.

Attributes

Inherited attributes

See ParamFreeBaseModel for more information on the attributes.

Additional attributes

  • mu (np.array): intercept

  • beta (np.array): effect size

  • model_name (str): model to use (BayesA, BayesB or BayesC)

  • n_iter (int): iterations for sampling

  • burn_in (int): warmup/burnin for sampling

Parameters
  • task (str) –

  • model_name (str) –

  • encoding (str) –

  • n_iter (int) –

  • burn_in (int) –

standard_encoding = 012
possible_encodings = ['101']
fit(self, X, y)

Implementation of fit function for Bayesian alphabet imported from R.

See ParamFreeBaseModel for more information.

Parameters
  • X (numpy.array) –

  • y (numpy.array) –

Return type

numpy.array

predict(self, X_in)

Implementation of predict function for Bayesian alphabet model imported from R.

See ParamFreeBaseModel for more information.

Parameters

X_in (numpy.array) –

Return type

numpy.array