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Approximate Bayesian Computation yang Kuat (Robust Approximate Bayesian Computation)

Robust ABC memperluas Approximate Bayesian Computation standar untuk menangani pencilan (outlier), spesifikasi model yang salah (model misspecification), dan sensitivitas terhadap pilihan statistik ringkasan. Dengan mengganti ukuran jarak konvensional dengan alternatif yang kuat — seperti skor komposit, statistik yang dipangkas (trimmed statistics), atau kemungkinan sintetis (synthetic likelihoods) — ia melindungi inferensi posterior agar tidak terdistorsi oleh observasi atipikal atau simulator yang tidak sempurna.

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Sumber

  1. Ruli, E., Sartori, N. & Ventura, L. (2016). Approximate Bayesian computation with composite score functions. Statistics and Computing, 26(3), 679–692. DOI: 10.1007/s11222-015-9551-z
  2. Frazier, D. T., Drovandi, C. & Nott, D. J. (2020). Robust Approximate Bayesian Inference with Synthetic Likelihood. Journal of Computational and Graphical Statistics, 30(4), 958–976. DOI: 10.1080/10618600.2021.1875839

Cara menyitasi halaman ini

ScholarGate. (2026, June 3). Robust Approximate Bayesian Computation. ScholarGate. https://scholargate.app/id/bayesian/robust-approximate-bayesian-computation

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ScholarGateRobust Approximate Bayesian Computation (Robust Approximate Bayesian Computation). Diakses 2026-06-15 dari https://scholargate.app/id/bayesian/robust-approximate-bayesian-computation · Set data: https://doi.org/10.5281/zenodo.20539026