Generalized Linear Models

class pymc3.glm.linear.LinearComponent(x, y, intercept=True, labels=None, priors=None, vars=None, name='', model=None)

Creates linear component, y_est is accessible via attribute

Parameters:

• name (str - name, associated with the linear component) –
• x (pd.DataFrame or np.ndarray) –
• y (pd.Series or np.array) –
• intercept (bool - fit with intercept or not?) –
• labels (list - replace variable names with these labels) –
• priors (dict - priors for coefficients) –

  use Intercept key for defining Intercept prior

  defaults to Flat.dist()

  use Regressor key for defining default prior for all regressors

  defaults to Normal.dist(mu=0, tau=1.0E-6)

• vars (dict - random variables instead of creating new ones) –

class pymc3.glm.linear.GLM(x, y, intercept=True, labels=None, priors=None, vars=None, family='normal', name='', model=None)

Creates glm model, y_est is accessible via attribute

Parameters:

• name (str - name, associated with the linear component) –
• x (pd.DataFrame or np.ndarray) –
• y (pd.Series or np.array) –
• intercept (bool - fit with intercept or not?) –
• labels (list - replace variable names with these labels) –
• priors (dict - priors for coefficients) –

  use Intercept key for defining Intercept prior

  defaults to Flat.dist()

  use Regressor key for defining default prior for all regressors

  defaults to Normal.dist(mu=0, tau=1.0E-6)

• init (dict - test_vals for coefficients) –
• vars (dict - random variables instead of creating new ones) –
• family (pymc3..families object) –