Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель регрессии с цензурированием Тобіта× | Регрессия отрицательного биномиального распределения× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1958 | 2011 |
| Автор метода≠ | James Tobin | Hilbe (textbook treatment); generalized linear model framework |
| Тип≠ | Censored regression (limited dependent variable) | Generalized linear model for count data |
| Основополагающий источник≠ | Tobin, J. (1958). Estimation of Relationships for Limited Dependent Variables. Econometrica, 26(1), 24-36. DOI ↗ | Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press. DOI ↗ |
| Другие названия | censored regression, limited dependent variable model, Tobit Modeli (Sansürlü Regresyon) | NB regression, NB2 regression, negatif binom regresyonu |
| Связанные | 4 | 4 |
| Сводка≠ | The Tobit model is a regression for outcomes that are censored at a threshold, estimating the relationship by maximum likelihood. Introduced by James Tobin in 1958, it addresses the pile-up of observations at a limit (typically zero) in data such as spending, wages, or duration. | 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. |
| ScholarGateНабор данных ↗ |
|
|