Time series clustering with Dirichlet process mixtures of ARMA models
| Project/Area Number |
22500261
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | Hiroshima City University |
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Principal Investigator |
SUEMATSU Nobuo 広島市立大学, 情報科学研究科, 准教授 (70264942)
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| Project Period (FY) |
2010 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2012: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2011: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2010: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 時系列解析 / マルコフ連鎖モンテカルロ法 / ディリクレ過程 / ARMAモデル / ディリクレ過程混合モデル / 時系列クラスタリング / 自然共役事前分布 |
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| Research Abstract |
ARMA models are parsimonious stochastic models for time series. Given a set of time series, we can cluster them by regarding that they were drawn from a mixture of ARMA models and by fitting the model to them, where if the mixture model is a Dirichlet process mixture, the number of the clusters can be simultaneously estimated. In this work, we have developed a Markov Chain Monte Carlo method to fit a Dirichlet process mixture of ARMA models to a set of time series.
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Report
(4 results)
Research Products
(21 results)
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[Journal Article] 階層隠れCRF2010
Author(s)
玉田 寛尚,林 朗,末松 伸朗,岩田一貴
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Journal Title
電子情報通信学会論文誌 D
Volume: Vol.J93-D, No.12
Pages: 2610-2619
NAID
Related Report
Peer Reviewed
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