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dc.contributor.author구유미-
dc.creator구유미-
dc.date.accessioned2016-08-26T03:08:45Z-
dc.date.available2016-08-26T03:08:45Z-
dc.date.issued2003-
dc.identifier.otherOAK-000000003470-
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/194364-
dc.identifier.urihttp://dcollection.ewha.ac.kr/jsp/common/DcLoOrgPer.jsp?sItemId=000000003470-
dc.description.abstract확률 미분방정식에 의해 정의된 비정상 affine diffusion process의 관심 모수를 추정함에 있어 새로운 Instrumental Variable estimator를 고려한다. 제시된 IV estimator의 pivotal quantity가 대표본 에서 Gaussian 분포를 따르므로, IV estimator를 사용한 관심 모수에 대한 근사 confidence interval과 근사 단위근(unit root) test를 구할 수 있다. 본 논문에서는 Monte-Carlo simulation을 통해, 비정상 affine 모형에서 sign-type IV estimator가 기존의 최소제곱추정량(Least square estimator) 보다 더 효과적이라는 사실을 확인하였다. ; We consider a new instrumental variable(IV) estimator of the parameter of the affine diffusion processes, defined by the possibly non-sationary stochastic differential equations. Because the pivotal statistic of proposed estimator has an asymptotic Gaussian distribution, we can construct the asymptotic confidence intervals and the tests for the parameter . Monte-Carlo simulation for the affine diffusion process shows that the proposed IV estimator provides a useful alternative to the least square estimator(LSE) for near non-stationary processes.-
dc.description.tableofcontentsABSTRACT = iv I.Introduction = 1 II. Sign-type IV Estimator for the Diffusion Model = 4 III.Finite Sample Properties of Cauchy Estimator = 7 IV.Results of Monte-Carlo Simulation = 12 4.1 Configuration of the simulation 4.2 Model : Affine model 4.3 Simulation results V.Discussion = 23 APPENDIX A. Girsanov Theorem = 24 APPENDIX B. S-PLUS Program Code = 25 REFERENCES = 28 KOREAN ABSTRACT = 30 감사의글-
dc.formatapplication/pdf-
dc.format.extent569155 bytes-
dc.languageeng-
dc.publisher이화여자대학교 대학원-
dc.titleA simulation study for affine diffusion model-
dc.typeMaster's Thesis-
dc.identifier.thesisdegreeMaster-
dc.identifier.major대학원 통계학과-
dc.date.awarded2003. 2-
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