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, linear regression, mixed model | linear regression, 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 GLIMMIX, PROC LOGISTIC (for regression with categorical variables) |
Command in Stata | regress | glm |
Command in SPSS | regression, glm | genlin, logistic regression |
Function in Wolfram Language & Mathematica | LinearModelFit[][2] | GeneralizedLinearModelFit[][3] |
Command in EViews | ls |
- ↑ McCullagh, Peter; Nelder, John (1989). Generalized Linear Models, Second Edition. Boca Raton: Chapman and Hall/CRC. ISBN 0-412-31760-5.
- ↑ LinearModelFit, Wolfram Language Documentation Center.
- ↑ GeneralizedLinearModelFit, Wolfram Language Documentation Center.
References
- McCullagh, Peter; Nelder, John (1989). Generalized Linear Models, Second Edition. Boca Raton: Chapman and Hall/CRC. ISBN 0-412-31760-5.
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