Parametric versus Semi/nonparametric Regression Models Course Topics Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the ...

How Homoskedasticity Works Homoskedasticity is one assumption of linear regression modeling, and data of this type work well with the least squares method.

Here's how to run both simple and multiple linear regression in Google Sheets using the built-in LINEST function. No add-ons or coding required.

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

We analyze linear panel regression models with interactive fixed effects and predetermined regressors, for example lagged-dependent variables. The first-order asymptotic theory of the least squares ...

We also extend the work to partially linear models when the reponse is related to some additional covariate. Statistica Sinica endeavors to meet the needs of statisticians faced with a rapidly ...