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A Monte Carlo study on a new test for unit roots in a seasonal autoregressive model
- Title
- A Monte Carlo study on a new test for unit roots in a seasonal autoregressive model
- Authors
- 오유진
- Issue Date
- 1997
- Department/Major
- 대학원 통계학과
- Keywords
- Monte Carlo; 시계열 자료; OLSE; median-unbiased
- Publisher
- The Graduate school of Ewha Women's University
- Degree
- Master
- Abstract
- 시계열 자료에서 단위근 검정시 OLSE(ordinary least square estimator)에 근거한 통계량을 많이 사용해왔다. 본 논문에서는 OLSE에 근거한 통계량의 단점을 보완하여 Cauchy-type estimator라 명명한 추정량을 제시하였다.
제시된 추정량은 median-unbiased 되어있고, 그 통계량은 극한 분포가 정규분포라는 장점이 있다. 그리고 Monte-Carlo simulation을 보면 부분적으로 OLSE에 근거한 테스트보다 부분적으로 더 powerful 하다.;For a seasonal autoregressive process, we propose a new estimator whose pivotal statistic has a standard normal limiting distribution for all range of autoregressive parameter . The proposed estimator is approximately median-unbiased. For seasonal time series, the new estimator gives us unit root tests which has the limiting normal distribution. A Monte-Carlo simulation shows that the proposed tests for unit root are locally more powerful than the tests based on the ordinary least squares estimator.
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