Comparison of general and generalized linear models
 |
| General linear model | Generalized linear model | |
|---|---|---|
| Typical estimation method | Least squares, best linear unbiased prediction | Maximum likelihood or Bayesian |
| Special cases | ANOVA, ANCOVA, MANOVA, MANCOVA, ordinary least squares, mixed model, t-test, F-test | ordinary least squares, logistic regression, Poisson regression, gamma regression[1] |
| Function in R | lm() | glm() |
| Function in Matlab | mvregress() | glmfit() |
| Procedure in SAS | PROC GLM, PROC MIXED | PROC GENMOD (PROC LOGISTIC for logistic regression only) |
| Command in Stata | regress | glm |
| Command in SPSS | regression, glm | genlin, logistic regression |
| Function in Mathematica | LinearModelFit[] | GeneralizedLinearModelFit[] |
| Command in EViews | ls |
- ^ McCullagh, Peter (1989). Generalized Linear Models, Second Edition. Boca Raton: Chapman and Hall/CRC. ISBN 0-412-31760-5.
{{cite book}}: Unknown parameter|coauthors=ignored (|author=suggested) (help)
References
- McCullagh, Peter (1989). Generalized Linear Models, Second Edition. Boca Raton: Chapman and Hall/CRC. ISBN 0-412-31760-5.
{{cite book}}: Unknown parameter|coauthors=ignored (|author=suggested) (help)
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