Kigezo cha Taarifa cha Bayesian (BIC)
Kigezo cha Taarifa cha Bayesian ni kigezo cha kuchagua modeli kinachotokana na nadharia ya taarifa ambacho kinakadiri kulinganisha modeli za Bayesian. Kiletwa na Gideon Schwarz mwaka 1978, BIC huadhibu ugumu wa modeli kwa uzito zaidi kuliko AIC kwa kutumia adhabu inayotegemea ukubwa wa sampuli, na kuifanya ifae sana katika kutambua muundo halisi wa data.
Soma mbinu kamili
Ingia kwa akaunti ya bure ili kusoma sehemu hii.
Method map
The neighbourhood of related methods — select a node to explore.
Vyanzo
- Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6(2), 461-464. DOI: 10.1214/aos/1176344136 ↗
- Burnham, K. P., & Anderson, D. R. (2002). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (2nd ed.). New York: Springer. DOI: 10.2307/3802723 ↗
- Kass, R. E., & Raftery, A. E. (1995). Bayes factors. Journal of the American Statistical Association, 90(430), 773-795. DOI: 10.1080/01621459.1995.10476572 ↗
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 3). Bayesian Information Criterion. ScholarGate. https://scholargate.app/sw/model-evaluation/bayesian-information-criterion
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- R² iliyorekebishwa (R²_adj)Tathmini ya Modeli↔ compare
- Kigezo cha Taarifa cha Akaike (AIC)Tathmini ya Modeli↔ compare
- Kosa la Wastani Lililopigwa Mraba (MSE)Tathmini ya Modeli↔ compare
- R-squared (R²)Tathmini ya Modeli↔ compare
Imerejelewa na
Umeona tatizo kwenye ukurasa huu? Ripoti au pendekeza marekebisho →