کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5096107 1376504 2014 24 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Beta-product dependent Pitman-Yor processes for Bayesian inference
ترجمه فارسی عنوان
فرایندهای پیتمن-یور وابسته به بتا محصول برای استنتاج بیزی
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آمار و احتمال
چکیده انگلیسی
Multiple time series data may exhibit clustering over time and the clustering effect may change across different series. This paper is motivated by the Bayesian non-parametric modelling of the dependence between clustering effects in multiple time series analysis. We follow a Dirichlet process mixture approach and define a new class of multivariate dependent Pitman-Yor processes (DPY). The proposed DPY are represented in terms of vectors of stick-breaking processes which determine dependent clustering structures in the time series. We follow a hierarchical specification of the DPY base measure to account for various degrees of information pooling across the series. We discuss some theoretical properties of the DPY and use them to define Bayesian non-parametric repeated measurement and vector autoregressive models. We provide efficient Monte Carlo Markov Chain algorithms for posterior computation of the proposed models and illustrate the effectiveness of the method with a simulation study and an application to the United States and the European Union business cycle.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Econometrics - Volume 180, Issue 1, May 2014, Pages 49-72
نویسندگان
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