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معيار المعلومات البايزي (BIC)×المعامل التحديد المعدل (R²_adj)×
المجالتقييم النماذجتقييم النماذج
العائلةMCDMMCDM
سنة النشأة19781961
صاحب الطريقةGideon E. SchwarzHenri Theil
النوعBayesian model selection metricPenalized goodness-of-fit metric
المصدر التأسيسيSchwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6(2), 461-464. DOI ↗Theil, H. (1961). Economic Forecasts and Policy. Amsterdam: North-Holland Publishing Company. link ↗
الأسماء البديلةBIC, Schwarz criterion, Schwarz information criterionAdjusted R², R²_adj
ذات صلة45
الملخصThe Bayesian Information Criterion is an information-theoretic model selection criterion that approximates Bayesian model comparison. Introduced by Gideon Schwarz in 1978, BIC penalizes model complexity more heavily than AIC by using a sample-size-dependent penalty, making it particularly suitable for identifying the true underlying model structure.Adjusted R² is a corrected version of the coefficient of determination that accounts for the number of predictors in a regression model. Introduced by Henri Theil in 1961, it addresses the fundamental limitation of standard R²: the tendency to increase whenever any predictor is added, regardless of whether that predictor contributes meaningfully to explaining the target variable.
ScholarGateمجموعة البيانات
  1. v1
  2. 3 المصادر
  3. PUBLISHED
  1. v1
  2. 3 المصادر
  3. PUBLISHED

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ScholarGateقارن الطرق: Bayesian Information Criterion · Adjusted R-squared. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare