Before building my model, I want to step back to offer an easy-to-understand definition of linear regression and why it’s vital to analyzing data. What is linear regression?

Course Topics 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 ...

Generalized Linear Models Generalized Linear Models Course Topics Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, ...

According to the genetic features of seed characters, two genetic models for mapping quantitative trait loci (QTLs) of crop seed traits are proposed, with inclusion of maternal effects, embryo or ...

Diet models based on goal programming (GP) are valuable tools in designing diets that comply with nutritional, palatability and cost constraints.

Lindley and Smith (1972), using a hierarchical form of prior structure, derived Bayesian alternatives to least squares estimates for the linear model. This paper examines the Bayesian model in more ...