کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1150433 | 957932 | 2009 | 14 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Bayesian inference for circular distributions with unknown normalising constants Bayesian inference for circular distributions with unknown normalising constants](/preview/png/1150433.png)
Very often, the likelihoods for circular data sets are of quite complicated forms, and the functional forms of the normalising constants, which depend upon the unknown parameters, are unknown. This latter problem generally precludes rigorous, exact inference (both classical and Bayesian) for circular data.Noting the paucity of literature on Bayesian circular data analysis, and also because realistic data analysis is naturally permitted by the Bayesian paradigm, we address the above problem taking a Bayesian perspective. In particular, we propose a methodology that combines importance sampling and Markov chain Monte Carlo (MCMC) in a very effective manner to sample from the posterior distribution of the parameters, given the circular data. With simulation study and real data analysis, we demonstrate the considerable reliability and flexibility of our proposed methodology in analysing circular data.
Journal: Journal of Statistical Planning and Inference - Volume 139, Issue 12, 1 December 2009, Pages 4179–4192