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\n  \n 2026\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n The EM algorithm for variance component estimation in multivariate Fay-Herriot model.\n \n \n \n \n\n\n \n Angkunsit, A.; and Suntornchost, J.\n\n\n \n\n\n\n Communications in Statistics - Simulation and Computation, 55(3): 810–840. 2026.\n Cited by: 1\n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@ARTICLE{Angkunsit2026,\n\tauthor = {Angkunsit, Annop and Suntornchost, Jiraphan},\n\ttitle = {The {EM} algorithm for variance component estimation in multivariate {Fay-Herriot} model},\n\tyear = {2026},\n\tjournal = {Communications in Statistics - Simulation and Computation},\n\tvolume = {55},\n\tnumber = {3},\n\tpages = {810--840},\n\tdoi = {10.1080/03610918.2024.2417809},\n\turl = {https://www.tandfonline.com/doi/full/10.1080/03610918.2024.2417809},\n\ttype = {Article},\n\tpublication_stage = {Final},\n\tsource = {Scopus},\n\tnote = {Cited by: 1}\n}\n\n
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\n  \n 2025\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n Robust extension of the multivariate Fay-Herriot model for data with outliers.\n \n \n \n \n\n\n \n Angkunsit, A.; and Suntornchost, J.\n\n\n \n\n\n\n Journal of Survey Statistics and Methodology,smaf026. 2025.\n Cited by: 0\n\n\n\n
\n\n\n\n \n \n \"RobustPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@ARTICLE{Angkunsit2025,\n\tauthor = {Angkunsit, Annop and Suntornchost, Jiraphan},\n\ttitle = {Robust extension of the multivariate {Fay-Herriot} model for data with outliers},\n\tyear = {2025},\n\tjournal = {Journal of Survey Statistics and Methodology},\n\tvolume = {},\n\tnumber = {},\n\tpages = {smaf026},\n\tdoi = {10.1093/jssam/smaf026},\n\turl = {https://doi.org/10.1093/jssam/smaf026},\n\ttype = {Article},\n\tpublication_stage = {Final},\n\tsource = {Scopus},\n\tnote = {Cited by: 0}\n}\n\n
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\n \n\n \n \n \n \n \n \n Adjusted maximum likelihood method based on shrinkage factor bias reduction for multivariate Fay-Herriot model.\n \n \n \n \n\n\n \n Angkunsit, A.; and Suntornchost, J.\n\n\n \n\n\n\n Australian & New Zealand Journal of Statistics, 67(3): 349–366. 2025.\n Cited by: 0\n\n\n\n
\n\n\n\n \n \n \"AdjustedPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@ARTICLE{Angkunsit2025,\n\tauthor = {Angkunsit, Annop and Suntornchost, Jiraphan},\n\ttitle = {Adjusted maximum likelihood method based on shrinkage factor bias reduction for multivariate {Fay-Herriot} model},\n\tyear = {2025},\n\tjournal = {Australian \\& New Zealand Journal of Statistics},\n\tvolume = {67},\n\tnumber = {3},\n\tpages = {349--366},\n\tdoi = {10.1111/anzs.70021},\n\turl = {https://onlinelibrary.wiley.com/doi/abs/10.1111/anzs.70021},\n\ttype = {Article},\n\tpublication_stage = {Final},\n\tsource = {Scopus},\n\tnote = {Cited by: 0}\n}\n\n
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\n  \n 2022\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n Adjusted maximum likelihood method for multivariate Fay-Herriot model.\n \n \n \n \n\n\n \n Angkunsit, A.; and Suntornchost, J.\n\n\n \n\n\n\n Journal of Statistical Planning and Inference, 219: 231–249. 2022.\n Cited by: 8\n\n\n\n
\n\n\n\n \n \n \"AdjustedPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@ARTICLE{Angkunsit2022,\n\tauthor = {Angkunsit, Annop and Suntornchost, Jiraphan},\n\ttitle = {Adjusted maximum likelihood method for multivariate {Fay-Herriot} model},\n\tyear = {2022},\n\tjournal = {Journal of Statistical Planning and Inference},\n\tvolume = {219},\n\tnumber = {},\n\tpages = {231--249},\n\tdoi = {10.1016/j.jspi.2021.12.010},\n\turl = {https://www.sciencedirect.com/science/article/pii/S0378375821001348},\n\ttype = {Article},\n\tpublication_stage = {Final},\n\tsource = {Scopus},\n\tnote = {Cited by: 8}\n}\n\n
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\n \n\n \n \n \n \n \n \n Modelling the household debts in Thailand using Fay-Herriot models.\n \n \n \n \n\n\n \n Angkunsit, A.; and Suntornchost, J.\n\n\n \n\n\n\n The Journal of Applied Science, 21(1): 1–13. 2022.\n Cited by: 0\n\n\n\n
\n\n\n\n \n \n \"ModellingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@ARTICLE{Angkunsit2022,\n\tauthor = {Angkunsit, Annop and Suntornchost, Jiraphan},\n\ttitle = {Modelling the household debts in {Thailand} using {Fay-Herriot} models},\n\tyear = {2022},\n\tjournal = {The Journal of Applied Science},\n\tvolume = {21},\n\tnumber = {1},\n\tpages = {1--13},\n\tdoi = {10.14416/j.appsci.2022.01.001},\n\turl = {https://ph01.tci-thaijo.org/index.php/JASCI/article/view/244482},\n\ttype = {Article},\n\tpublication_stage = {Final},\n\tsource = {},\n\tnote = {Cited by: 0}\n}\n\n
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\n  \n 2021\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Bivariate Fay-Herriot models with application to Thai socio-economic data.\n \n \n \n \n\n\n \n Angkunsit, A.; and Suntornchost, J.\n\n\n \n\n\n\n Asian Health, Science and Technology Reports, 29(1): 36–49. 2021.\n Cited by: 8\n\n\n\n
\n\n\n\n \n \n \"BivariatePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@ARTICLE{Angkunsit2021,\n\tauthor = {Angkunsit, Annop and Suntornchost, Jiraphan},\n\ttitle = {Bivariate {Fay-Herriot} models with application to {Thai} socio-economic data},\n\tyear = {2021},\n\tjournal = {Asian Health, Science and Technology Reports},\n\tvolume = {29},\n\tnumber = {1},\n\tpages = {36--49},\n\tdoi = {10.14456/nujst.2021.3},\n\turl = {https://ph01.tci-thaijo.org/index.php/JASCI/article/view/244482},\n\ttype = {Article},\n\tpublication_stage = {Final},\n\tsource = {},\n\tnote = {Cited by: 8}\n}\n\n
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\n  \n 2018\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Variable selection in multivariate linear regression models subject to sampling errors.\n \n \n \n \n\n\n \n Angkunsit, A.; and Suntornchost, J.\n\n\n \n\n\n\n Chamchuri Journal of Mathematics, 10: 28–52. 2018.\n Cited by: 0\n\n\n\n
\n\n\n\n \n \n \"VariablePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@ARTICLE{Angkunsit2018,\n\tauthor = {Angkunsit, Annop and Suntornchost, Jiraphan},\n\ttitle = {Variable selection in multivariate linear regression models subject to sampling errors},\n\tyear = {2018},\n\tjournal = {Chamchuri Journal of Mathematics},\n\tvolume = {10},\n\tnumber = {},\n\tpages = {28--52},\n\tdoi = {},\n\turl = {https://ph02.tci-thaijo.org/index.php/cjm/article/view/230780},\n\ttype = {Article},\n\tpublication_stage = {Final},\n\tsource = {},\n\tnote = {Cited by: 0}\n}
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