Poisson regression, Advanced Statistics

Assignment Help:

Poisson regression

In case of Poisson regression we use ηi = g(µi) = log(µi) and a variance V ar(Yi) = φµi. The case φ = 1 corresponds to standard Poisson model. Poisson regression is used when the response to model is counts which typically follow a Poisson distribution. Examples include colony counts for bacteria or viruses, accidents, equipment failures, insurance claims, incidence of disease. Interest often lies in estimating a rate of incidence and determining its relationship to a set of explanatory variables. Again, an IRLS procedure is used to ?nd the MLE estimators of the β coeffcients. When we can not assume φ = 1, (this is the case of over- or under- dispersion discussed in McCullagh and Nelder (1989)), the iterative procedure is changed to so called "quasi-likelihood estimation". Finally in this section, we shall also mention shortly the extension of GLM to GAM.


Related Discussions:- Poisson regression

Explain lie factor, Lie factor : A measure suggested by Tufte for judging t...

Lie factor : A measure suggested by Tufte for judging the honesty of the graphical presentation of data. Which can be calculated as follows   The values close to one are desir

Define non linear mapping (nlm), Non linear mapping (NLM ) is a technique f...

Non linear mapping (NLM ) is a technique for obtaining a low-dimensional representation of the set of multivariate data, which operates by minimizing a function of the differences

Greenhouse geissercorrection, Greenhouse geissercorrection is the method o...

Greenhouse geissercorrection is the method of adjusting the degrees of freedom of the within- subject F-tests in the analysis of the variance of longitudinal data so as to allow t

Explain historical controls, Historical controls : The group of patients tr...

Historical controls : The group of patients treated in the past with the standard therapy, taken in use as the control group for evaluating the new treatment on the present patient

White''s general heteroscedasticity test, The Null Hypothesis - H0:  γ 1 =...

The Null Hypothesis - H0:  γ 1 = γ 2 = ...  =  0  i.e.  there is no heteroscedasticity in the model The Alternative Hypothesis - H1:  at least one of the γ i 's are not equal

Assignment, Hi there i have send mail on info@expertminds regarding assignm...

Hi there i have send mail on info@expertminds regarding assignment, i am waiting nearly 45 minutes for reply

Exponential family, A family of the probability distributions of the form g...

A family of the probability distributions of the form given as   here θ is the parameter and a, b, c, d are the known functions. It includes the gamma distribution, normal dis

frequentist inference, The approach to statistics based on a frequency vie...

The approach to statistics based on a frequency view of probability in which it is supposed that it is possible to consider an in?nite sequence of the independent repetitions of th

Non parametric maximum likelihood (npml), Non parametric maximum likelihood...

Non parametric maximum likelihood (NPML) is a likelihood approach which does not need the specification of the full parametric family for the data. Usually, the non parametric max

Explain Geometric distribution, Geometric distribution: The probability di...

Geometric distribution: The probability distribution of the number of trials (N) before the first success in the sequence of Bernoulli trials. Specifically the distribution is can

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd