کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5096913 | 1376557 | 2010 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Stochastic model specification search for Gaussian and partial non-Gaussian state space models
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Model specification for state space models is a difficult task as one has to decide which components to include in the model and to specify whether these components are fixed or time-varying. To this aim a new model space MCMC method is developed in this paper. It is based on extending the Bayesian variable selection approach which is usually applied to variable selection in regression models to state space models. For non-Gaussian state space models stochastic model search MCMC makes use of auxiliary mixture sampling. We focus on structural time series models including seasonal components, trend or intervention. The method is applied to various well-known time series.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Econometrics - Volume 154, Issue 1, January 2010, Pages 85-100
Journal: Journal of Econometrics - Volume 154, Issue 1, January 2010, Pages 85-100
نویسندگان
Sylvia Frühwirth-Schnatter, Helga Wagner,