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Updated: Jan 11, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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Published on: July 3, 2020

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计算时间序列的GARMA模型中的顺序选择:贝叶斯的视角

Katerine Zuniga Lastra1, Guilherme Pumi1, Taiane Schaedler Prass1

  • 1Instituto de Matemática e Estatística and Programa de Pós-Graduação em Estatística, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.

Journal of applied statistics
|November 12, 2025
PubMed
概括

这项研究引入了贝叶斯的方法来选择在一般自回归移动平均 (GARMA) 模型中计数时间序列的顺序选择. 与传统的信息标准相比,可逆跳马尔科夫链蒙特卡洛方法可以改善模型识别.

关键词:
62F10 它们是什么?62F15 一个很好的例子.62J02 这是一个很好的例子.62M1010 它们是什么?贝叶斯分析是贝叶斯分析.计数时间序列时间序列.回归模型是一种回归模型.可逆跳转马尔科夫链的马尔科夫链.

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