If you have experience with R or want a quick way to generate a regression with statsmodels using a pandas DataFrame, you can ...

Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...

Generalized linear models are widely used by data analysts. However, the choice of the link function is often made arbitrarily. Here we permit the data to estimate the link function by incorporating ...

Linear mixed model (LMM) methodology is a powerful technology to analyze models containing both the fixed and random effects. The model was first proposed to estimate genetic parameters for unbalanced ...

This article describes three approximation methods I used to solve the growth model (Model 1) studied by the National Bureau of Economic Research's nonlinear rational-expectations-modeling group ...