statsmodels.multivariate.multivariate_ols._MultivariateOLS

class statsmodels.multivariate.multivariate_ols._MultivariateOLS(endog, exog, missing='none', hasconst=None, **kwargs)[source]

Multivariate linear model via least squares

Parameters:

endog : array_like

Dependent variables. A nobs x k_endog array where nobs is the number of observations and k_endog is the number of dependent variables

exog : array_like

Independent variables. A nobs x k_exog array where nobs is the number of observations and k_exog is the number of independent variables. An intercept is not included by default and should be added by the user (models specified using a formula include an intercept by default)

Attributes

endog (array) See Parameters.
exog (array) See Parameters.

Methods

fit([method]) Fit a model to data.
from_formula(formula, data[, subset, drop_cols]) Create a Model from a formula and dataframe.
predict(params[, exog]) After a model has been fit predict returns the fitted values.