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)

endog

See Parameters.

Type

array

exog

See Parameters.

Type

array

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.

Attributes

endog_names

Names of endogenous variables

exog_names

Names of exogenous variables