The literature of log linear models and logistic regression is surveyed from a contemporary point of view. A matrix formulation of the general log linear model for product-multinomial random counts is ...

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, ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

As the title “Practical Regression” suggests, these notes are a guide to performing regression in practice. This note explains how to choose between log and linear specification. The note emphasizes ...

In this chapter, we propose a log-linear model for the biases observed when analyzing model communities data. Our model expands the recent work from McLaren, Willis and Callahan (MWC) [eLife, 8:e46923 ...

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, ...

Imrey, Koch, Stokes and collaborators (1981) have reviewed the literature of log linear and logistic categorical data modelling, and presented a matrix formulation of log linear models parallel to the ...