Statistical Sequential Testing and Change-point Detection on Nonstationarity
Project/Area Number |
24530226
|
Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Economic statistics
|
Research Institution | Yokohama National University |
Principal Investigator |
NAGAI KEIJI 横浜国立大学, 国際社会科学研究院, 教授 (50311866)
|
Project Period (FY) |
2012-04-01 – 2015-03-31
|
Project Status |
Completed (Fiscal Year 2014)
|
Budget Amount *help |
¥5,070,000 (Direct Cost: ¥3,900,000、Indirect Cost: ¥1,170,000)
Fiscal Year 2014: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2013: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2012: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
|
Keywords | 自己回帰過程 / 分枝過程 / 統計的逐次探索 / 変化点問題 / 停止時刻 / 統計的意思決定論 / 局所漸近正規 / 局所漸近最適性 / 統計的逐次解析 / 停止時刻による統計解析 / 非定常時系列 / 分枝過程の臨界性 / 変化点探索 / 確率解析の応用 / 単位根検定 / 時間変更 / ベッセル過程 / 国際情報交換 |
Outline of Final Research Achievements |
In this research, assuming online observations of stochastic sequence, I established a sequential testing procedure for the detection of the existence of non-stationary state such as bubble in financial time series and a sequential change-point detection procedure for the detection of the change in a parameter in financial time series. I also developed a sequential testing procedure and a sequential change-point detection for the criticality of branching process, which is important in epidemiology and population statistics. In each case, some mathematical optimality and a method for numerical computation are developed.
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Report
(4 results)
Research Products
(3 results)