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 ...

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 ...

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

Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...