Statistical Sequential Analysis via Stochastic Calculus and It's Application
| Project/Area Number |
15K03395
|
|---|
| 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, 大学院国際社会科学研究院, 教授 (50311866)
|
|---|
| Project Period (FY) |
2015-04-01 – 2018-03-31
|
| Project Status |
Completed (Fiscal Year 2017)
|
| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2015: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
|
|---|
| Keywords | 時系列解析 / 統計的逐次解析 / 停止時刻 / ｐ階自己回帰過程 / 単位根検定 / 局所漸近正規 / 汎関数中心極限定理 / 確率解析 / 時系列過程 / Fisher情報量 / Bessel過程 / オンライン検知・探索 / オンライン意思決定 / ブラウン運動 / マルチンゲール中心極限定理 / 伊藤過程 / ベッセル過程 / パネルデータ / 早期検知・探索 / 早期意思決定 |
|---|
| Outline of Final Research Achievements |
We consider a sequentially observed unstable AR(p) process with a unit root or a near unit root and provide a sequential testing procedure corresponding to the augmented Dickey-Fuller test in non-sequential sampling. Modifying the stopping time for AR(1) in Lai and Siegmund (1983), we introduce a stopping time based on observed Fisher information for AR(p). The sequential testing procedure has LAN(local asymptotic normality), which can be shown by the time change of the score process using its quadratic variation in Ornstein-Uhlenbeck process. The asymptotic property of the stopping time is characterized by the Bessel process, which makes possible to obtain its asymptotic moments. A testing procedure using the quantile of the asymptotic distribution of the stopping time is a
|
Report
(4 results)
Research Products
(1 results)
