Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

Compared to standard linear regression, which predicts a single numeric value based only on a linear combination of predictor values, linear regression with interactions can handle more complex data ...

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

We introduce a fast stepwise regression method, called the orthogonal greedy algorithm (OGA), that selects input variables to enter a p-dimensional linear regression model (with p ≫ n, the sample size ...

Course TopicsLinear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the ...

Model building via linear regression models. Method of least squares, theory and practice. Checking for adequacy of a model, examination of residuals, checking outliers. Practical hand on experience ...

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, ...

Tao Chen, SEMIPARAMETRIC EFFICIENCY FOR CENSORED LINEAR REGRESSION MODELS WITH HETEROSKEDASTIC ERRORS, Econometric Theory, Vol. 34, No. 1 (February 2018), pp. 228-245 ...