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Mô phỏng hierarchy MCMC cho mô hình Satlns ~ end + ses + res + insured, BayesVL v0.6.5 trên 1042 quan sát thực

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  • Vuong, Quan-Hoang
  • La, Viet-Phuong

Abstract

Bài viết này (Note 2b) trình bày một mô hình và ứng dụng mô phỏng BayesVL v0.6.5 [1] trên môi trường R và Stan MCMC, cho bài toán thực tế [2] với dữ liệu thực tế, gồm 1042 điểm dữ liệu [3]. Nội dung của bài là một phần của tài liệu do AISDL biên soạn phục vụ hướng dẫn sử dụng “The BayesVL R Package”, nhằm thúc đẩy việc sử dụng phương pháp thống kê Bayesian trong KHXH&NV.

Suggested Citation

  • Vuong, Quan-Hoang & La, Viet-Phuong, 2019. "Mô phỏng hierarchy MCMC cho mô hình Satlns ~ end + ses + res + insured, BayesVL v0.6.5 trên 1042 quan sát thực," OSF Preprints dm467, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:dm467
    DOI: 10.31219/osf.io/dm467
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    References listed on IDEAS

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    1. Scutari, Marco, 2010. "Learning Bayesian Networks with the bnlearn R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 35(i03).
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