Toric models have been recently introduced in the analysis of statistical models for categorical data. The main improvement with respect to classical log-linear models is shown to be a simple representation of structural zeros. In this paper we analyze the geometry of toric models, showing that a toric model is the disjoint union of a number of log-linearmodels.Moreover, we discuss the connecti...

This paper will discuss the basic principles underlying the theory of generalized linear models and the advantages of using generalized linear models over more traditional methods of actuarial modeling. Generalized linear models offer the flexibility needed to model real world data that does not conform to the strict assumptions underlying these traditional methods. The second part ofthis paper...

Log-linear models represent nowadays the state-of-the-art in statistical machine translation. There, several models are combined altogether into a whole statistical approach. Finite-state transducers constitute a special type of statistical translation model whose interest has been proved in different translation tasks. The goal of this work is to introduce a finite-state framework for a log-li...

A review of the different approaches using the General Linear Model (GLM) to analyse multi-subject fMRI studies is presented. The first part of the paper attempts to expose the approaches with the least amount of statistic knowledge whilst the second part embeds those approaches in the GLM framework necessitating more statistical mathematical awareness, but enabling more advanced applications. ...

The study focuses on how socio-economic and demographic indicators affect fertilization sustainability (excessive amount of fertilization). Principally we aim to examine the significance magnitude of the effects of three socio-demographic variables such as traditional way of fertilization, rental land farming, and farmers’ younger age on over-fertilization in Bangladesh and other developing cou...

Given the importance of knowledge of species distribution for conservation and climate change management, continuous and progressive evaluation of the statistical models predicting species distributions is necessary. Current models are evaluated in terms of ecological theory used, the data model accepted and the statistical methods applied. Focus is restricted to Generalised Linear Models (GLM)...

In recent years, the class of generalized linear models has gained popularity as a statistical modeling tool. This popularity is due in part to the flexibility of generalized linear models in addressing a variety of statistical problems and to the availability of software to fit the models. The SAS system provides two new tools that fit generalized linear models. The GENMOD procedure in SAS/ST...

Frequentist approaches to making inferences about the variances of random cluster effects in hierarchical generalized linear models (HGLMs) for non-normal variables have several limitations. These include reliance on asymptotic theory, questionable properties of classical likelihood ratio tests when pseudo-likelihood methods are used for estimation, and a failure to account for uncertainty in t...

The crossover design involves observing the same response variate under different experimental conditions for each subject, and as such, is a special case of a repeated measures or multivariate data structure. The general multivariate linear model provides a natural framework for analysis of such data because generalizations to more complex structures are feasible and follow the same rationale....