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| Мултиномиална логистична регресия× | Логистична регресия× | |
|---|---|---|
| Област≠ | Иконометрия | Статистика за изследвания |
| Семейство≠ | Regression model | Process / pipeline |
| Година на възникване≠ | 1974 | 1958 |
| Създател≠ | McFadden | David Roxbee Cox |
| Тип≠ | Multinomial logistic regression | Method |
| Основополагащ източник≠ | McFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503 | Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗ |
| Други названия≠ | multinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon | logit model, binomial logistic regression, LR |
| Свързани≠ | 5 | 3 |
| Резюме≠ | Multinomial logistic regression is a maximum-likelihood method for a nominal (unordered) dependent variable with more than two categories. Building on McFadden's 1974 treatment of qualitative choice, it gives each category its own set of coefficients relative to a reference category. | Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science. |
| ScholarGateНабор от данни ↗ |
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