This general approach includes the special cases of the functional linear model, as well as functional Poisson regression and functional binomial regression. The latter leads to procedures for ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

In experimental statistics the usual method of estimating treatment effects is to introduce arbitrary linear restrictions among the treatment effects in order to obtain solutions of the normal ...

is the degrees of freedom associated with each parameter estimate. There is one degree of freedom unless the model is not full rank. In this case, any parameter that is confounded with previous ...

Generalized linear mixed model We use a binomial trait as an example to demonstrate the new methodology, although the method can be applied to other discrete traits.

What is a Generalized Linear Model? A traditional linear model is of the form where yi is the response variable for the i th observation. The quantity xi is a column vector of covariates, or ...

Since 1987, MCEER, formerly the Multidisciplinary Center for Earthquake Engineering Research (MCEER) and the National Center for Earthquake Engineering Research ( NCEER), has produced over 600 ...