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  • 标题:MODIFIED RECURSIVE BAYESIAN ALGORITHM FOR ESTIMATING TIME-VARYING PARAMETERS IN DYNAMIC LINEAR MODELS
  • 本地全文:下载
  • 作者:O. Olawale Awe ; A. Adedayo Adepoju
  • 期刊名称:Statistics in Transition
  • 印刷版ISSN:1234-7655
  • 电子版ISSN:2450-0291
  • 出版年度:2018
  • 卷号:19
  • 期号:2
  • 页码:239-258
  • DOI:10.21307/stattrans-2018-014
  • 出版社:Exeley Inc.
  • 摘要:Estimation in Dynamic Linear Models (DLMs) with Fixed Parameters (FPs) has been faced with considerable limitations due to its inability to capture the dynamics of most time-varying phenomena in econometric studies. An attempt to address this limitation resulted in the use of Recursive Bayesian Algorithms (RBAs) which is also affected by increased computational problems in estimating the Evolution Variance (EV) of the time-varying parameters. In this paper, we propose a modified RBA for estimating TVPs in DLMs with reduced computational challenges.
  • 关键词:discounted variance;dynamic models;granularity range;estimation algorithm
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