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Pengpurataan Model Bayes Berbilang Aras

Pengpurataan model Bayes berbilang aras (ML-BMA) memperluas pengpurataan model Bayes klasik kepada data yang dikumpulkan atau berstruktur hierarki. Daripada terikat pada satu spesifikasi model berbilang aras tunggal, ia mengira purata berwajaran ramalan dan anggaran parameter merentasi satu set model berbilang aras calon, dengan memberatkan setiap model mengikut kebarangkalian posteriornya berdasarkan data. Hasilnya mengambil kira secara serentak ketidakpastian dalam struktur pengumpulan, kesan tetap, kesan rawak, dan pemilihan kovariat.

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Sumber

  1. Hoeting, J. A., Madigan, D., Raftery, A. E. & Volinsky, C. T. (1999). Bayesian model averaging: A tutorial. Statistical Science, 14(4), 382-401. link
  2. Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955

Cara memetik halaman ini

ScholarGate. (2026, June 3). Multilevel Bayesian Model Averaging. ScholarGate. https://scholargate.app/ms/bayesian/multilevel-bayesian-model-averaging

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ScholarGateMultilevel Bayesian Model Averaging (Multilevel Bayesian Model Averaging). Dicapai 2026-06-15 daripada https://scholargate.app/ms/bayesian/multilevel-bayesian-model-averaging · Set data: https://doi.org/10.5281/zenodo.20539026