statsmodels.genmod.qif.QIF¶
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class
statsmodels.genmod.qif.
QIF
(endog, exog, groups, family=None, cov_struct=None, missing='none', **kwargs)[source]¶ Fit a regression model using quadratic inference functions (QIF).
QIF is an alternative to GEE that can be more efficient, and that offers different approaches for model selection and inference.
Parameters: endog : array-like
The dependent variables of the regression.
exog : array-like
The independent variables of the regression.
groups : array-like
Labels indicating which group each observation belongs to. Observations in different groups should be independent.
family : genmod family
An instance of a GLM family.
cov_struct : QIFCovariance instance
An instance of a QIFCovariance.
References
A. Qu, B. Lindsay, B. Li (2000). Improving Generalized Estimating Equations using Quadratic Inference Functions, Biometrika 87:4. www.jstor.org/stable/2673612
Attributes
endog_names
Names of endogenous variables exog_names
Names of exogenous variables Methods
estimate_scale
(params)Estimate the dispersion/scale. fit
([maxiter, start_params, tol, gtol, …])Fit a GLM to correlated data using QIF. from_formula
(formula, groups, data[, subset])Create a QIF model instance from a formula and dataframe. objective
(params)Calculate the gradient of the QIF objective function. predict
(params[, exog])After a model has been fit predict returns the fitted values.