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, ...

Linear regression remains a cornerstone of statistical analysis, offering a framework for modelling relationships between a dependent variable and one or more independent predictors. Over the past ...

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, ...

Last month we explored how to model a simple relationship between two variables, such as the dependence of weight on height 1. In the more realistic scenario of dependence on several variables, we can ...

Implementing LRR from scratch is harder than using a library like scikit-learn, but it helps you customize your code, makes it easier to integrate with other systems, and gives you a complete ...

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...

Keywords: Statistical analyses. Regression models. Post-earthquake ignitions. Data analyses. California. Ground shaking. Generalized linear mixed models. Goodness-of ...

Sankhyā: The Indian Journal of Statistics, Series B (1960-2002), Vol. 62, No. 3 (Dec., 2000), pp. 433-447 (15 pages) This paper discusses an econometric technique based on optimal control theory which ...