Generalized linear models, Advanced Statistics

Introduction to Generalized Linear Models (GLM) We introduce the notion of GLM as an extension of the traditional normal-theory-based linear regression models.

This will be very helpful in order to gain a general insight into all discussions till the end of this course since the speci?c models that will be discussed in details from now all, will turn out to be speci?c GLM. We already mentioned in the introductory lecture that when dealing with categorical data as output, it is not wise to model it (or for that matter, the probabilities for its particular categories) by using linear models. This is why one has tried to extend the Linear Models theory to make it suitable for such situations. There are at least two important aspects of the extension of the traditional normal- theory based linear regression model.

  • It allows the mean of a population to depend on a linear predictor through a nonlinear link function
  • The response probability distribution to be not necessarily normal but a member of the exponential family of distributions.

The set of generalized linear models is indeed quite large. These include: classical linear models with normal errors, logistic and probit models for binary categorical data, and log- linear models for multinomial data. Many other statistical models can also be shown to be
a particular GLM after choosing suitably the link function and the response probability distribution.

Posted Date: 2/27/2013 12:27:19 AM | Location : United States

Related Discussions:- Generalized linear models, Assignment Help, Ask Question on Generalized linear models, Get Answer, Expert's Help, Generalized linear models Discussions

Write discussion on Generalized linear models
Your posts are moderated
Related Questions
Cauchy distribution : The probability distribution, f (x), can be given as follows   where α is the position of the parameter (median) and the beta β a scale parameter. Moments

A test for equality of the variances of the two populations having normal distributions, based on the ratio of the variances of the sample of observations taken from each. Most fre

Chain-binomial models : Models arising in mathematical theory of the quite infectious diseases, which postulate that at any stage in the epidemic there are a certain number of the

MAREG is the software package for the analysis of the marginal regression models. The package permits the application of generalized estimating equations and the maximum likelihoo

Compliance : The extent to which the participants in a clinical trial follow trial protocol, for instance, following both the intervention regimen and trial procedures (clinical vi

A term commonly encountered in the analysis of the contingency tables. Such type of frequencies are the estimates of the values to be expected under hypothesis of interest. In a tw

The model which arises in the context of estimating the size of the closed population where individuals within the population could be identified only during some of the observatio

Persson Rootze ´n estimator  is an estimator for the parameters in the normal distribution when the sample is truncated so that all the observations under some fixed value C are re

Harris and Stevens forecasting is the method of making short term forecasts in the time series which is subject to abrupt changes in pattern and the transient effects. Instances o