3.9.1. statsmodels.regression.feasible_gls¶
Created on Tue Dec 20 20:24:20 2011
Author: Josef Perktold License: BSD-3
3.9.1.1. Functions¶
atleast_2dcols(x) |
3.9.1.2. Classes¶
GLS(endog, exog[, sigma, missing, hasconst]) |
Generalized least squares model with a general covariance structure. |
GLSHet(endog, exog[, exog_var, weights, link]) |
A regression model with an estimated heteroscedasticity. |
GLSHet2(endog, exog, exog_var[, sigma]) |
WLS with heteroscedasticity that depends on explanatory variables |
OLS(endog[, exog, missing, hasconst]) |
A simple ordinary least squares model. |
RegressionResults(model, params[, ...]) |
This class summarizes the fit of a linear regression model. |
WLS(endog, exog[, weights, missing, hasconst]) |
A regression model with diagonal but non-identity covariance structure. |