Ordinal regression and classification methods form a vital branch of statistical learning wherein the outcome variable possesses an inherent order. Unlike conventional classification problems, where ...

The goal of a machine learning regression problem is to predict a single numeric value, for example, predicting a person's income based on their age, height, years of education, and so on. There are ...

Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict a person's income based on their age, weight, current bank account ...

This article studies weighted, generalized, least squares estimators in simple linear regression with serially correlated errors. Closed-form expressions of weighted least squares estimators and ...

Andriy Blokhin has 5+ years of professional experience in public accounting, personal investing, and as a senior auditor with Ernst & Young. Thomas J Catalano is a CFP and Registered Investment ...