We consider generalized linear regression with many highly correlated regressors-for instance, digitized points of a curve on a spatial or temporal domain. We refer to this setting as signal ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

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 ...

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