Generalized linear models (GLMs) provide a unifying framework for analysing count data by relating a linear predictor to the expected value of a response variable through a suitable link function. In ...

Generally speaking, there are two types of outcomes (i.e. response) in statistical analysis: continuous and categorical responses. Linear Models (LM) are one of the most commonly used statistical ...

The actuarial methodology powering insurance risk models is advancing faster than most carriers realize. Here is what is ...

Linear mixed model (LMM) methodology is a powerful technology to analyze models containing both the fixed and random effects. The model was first proposed to estimate genetic parameters for unbalanced ...

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 ...