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النموذج الخطي المعمم (GLM)×الانحدار اللوجستي×
المجالالإحصاءإحصاء البحث
العائلةRegression modelProcess / pipeline
سنة النشأة19721958
صاحب الطريقةJohn A. Nelder & Robert W. M. WedderburnDavid Roxbee Cox
النوعRegression frameworkMethod
المصدر التأسيسيNelder, J. A., & Wedderburn, R. W. M. (1972). Generalized linear models. Journal of the Royal Statistical Society: Series A (General), 135(3), 370–384. DOI ↗Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗
الأسماء البديلةGLM, generalized regression, exponential family regression, link-function modellogit model, binomial logistic regression, LR
ذات صلة63
الملخصThe Generalized Linear Model is a unified regression framework that extends ordinary linear regression to outcomes from the exponential family — including binary, count, proportion, and continuous positive outcomes. A link function connects the linear predictor to the mean of the response, enabling principled modelling beyond the Gaussian case.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.
ScholarGateمجموعة البيانات
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  2. 2 المصادر
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  1. v1
  2. 2 المصادر
  3. PUBLISHED

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ScholarGateقارن الطرق: Generalized Linear Model · Logistic Regression. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare