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What are the differences between standard linear regression analysis vs the generalized linear models (GLMs).

What are the differences between standard linear regression analysis vs the generalized linear models (GLMs).

Math   Statistics-And-Probability   
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Answer #1

Generalized Linear Models(GLMs)

Each outcome Y of the dependent variables is assumed to be generated from particular distribution like Poisson, binomial, negative binomial etc.

It consist of three components

1) An exponential function of probability distribution.

2) A linear predictor.

3) A link function ie, expected value of y given in the below image.

In GLM we can't use least square method.

Standard Linear regression Analysis.

Linear regression is a linear approach to modelling the dependent and one or more independent variables.

The relationship is modelled using linear predictor functions which is unknown and it is calculated using the data.

Standard linear regression analysis can be performed using least sqaure method.

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