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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 Carlo시계열 자료OLSEmedian-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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