Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Gamma regresija (GLM)× | Negatīvā binomiālā regresija× | |
|---|---|---|
| Nozare≠ | Statistika | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1989 | 2011 |
| Autors≠ | McCullagh & Nelder (GLM framework) | Hilbe (textbook treatment); generalized linear model framework |
| Tips≠ | Generalized linear model | Generalized linear model for count data |
| Pirmavots≠ | McCullagh, P. & Nelder, J. A. (1989). Generalized Linear Models (2nd ed.). Chapman and Hall. DOI ↗ | Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press. DOI ↗ |
| Citi nosaukumi | gamma GLM, gamma generalized linear model, Gamma Regresyonu (GLM) | NB regression, NB2 regression, negatif binom regresyonu |
| Saistītās | 4 | 4 |
| Kopsavilkums≠ | Gamma regression is a generalized linear model that uses the gamma distribution to model a positive, right-skewed continuous outcome. Developed within the GLM framework of McCullagh and Nelder (1989), it is an alternative to ordinary linear regression for variables such as health-care costs, durations, and income. | Negative Binomial Regression is a generalized linear model for count outcomes that extends Poisson regression to handle overdispersion, where the variance of the counts exceeds their mean. Developed in the GLM tradition and treated in depth by Hilbe (2011), it adds a dispersion parameter so that inference stays valid when Poisson would understate the spread of the data. |
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