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Bayesian methods

Regressioni ya Lojistiki ya Bayesian

Regressioni ya lojistiki ya Bayesian ni modeli ya uainishaji inayotumia dhana ya Bayesian kwa uwezekano wa lojistiki (sigmoid) kwa matokeo ya binary au multinomial. Iliyotengenezwa ndani ya mfumo wa kabla ya habari hafifu iliyoandaliwa na Gelman, Jakulin, Pittau na Su (2008), huweka usambazaji wa kabla juu ya coefficients na huunganisha kabla hiyo na uwezekano wa data kutoa usambazaji kamili wa baada kwa kila kigezo — ikitoa uwezekano wa darasa uliohakikishiwa na kutokuwa na uhakika hata katika sampuli ndogo, mipangilio ya tukio adimu, au kesi za mgawanyiko kamili ambapo makadirio ya mara kwa mara ya kiwango cha juu cha uwezekano huanguka.

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  1. Gelman, A., Jakulin, A., Pittau, M. G. & Su, Y.-S. (2008). A Weakly Informative Default Prior Distribution for Logistic and Other Regression Models. Annals of Applied Statistics, 2(4), 1360–1383. DOI: 10.1214/08-AOAS191

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ScholarGate. (2026, June 1). Bayesian Logistic Regression. ScholarGate. https://scholargate.app/sw/bayesian/bayesian-logistic-regression

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ScholarGateBayesian Logistic Regression (Bayesian Logistic Regression). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/bayesian/bayesian-logistic-regression · Seti ya data: https://doi.org/10.5281/zenodo.20539026