• 제목/요약/키워드: semiparametric

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Long Memory Characteristics in the Korean Stock Market Volatility

  • Cho, Sinsup;Choe, Hyuk;Park, Joon Y
    • Communications for Statistical Applications and Methods
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    • 제9권3호
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    • pp.577-594
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    • 2002
  • For the estimation and test of long memory feature in volatilities of stock indices and individual companies semiparametric approach, Geweke and Porter-Hudak (1983), is employed. Empirical study supports the strong evidence of volatility persistence in Korean stock market. Most of indices and individual companies have the feature of long term dependence of volatility. Hence the short memory models are unable to explain the volatilities in Korean stock market.

A Generalized Partly-Parametric Additive Risk Model

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
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    • 제17권2호
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    • pp.401-409
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    • 2006
  • We consider a generalized partly-parametric additive risk model which generalizes the partly parametric additive risk model suggested by McKeague and Sasieni (1994). As an estimation method of this model, we propose to use the weighted least square estimation, suggested by Huffer and McKeague (1991), for Aalen's additive risk model by a piecewise constant risk. We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least squares method.

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Semiparametric Bayesian multiple comparisons for Poisson Populations

  • Cho, Jang Sik;Kim, Dal Ho;Kang, Sang Gil
    • Communications for Statistical Applications and Methods
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    • 제8권2호
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    • pp.427-434
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    • 2001
  • In this paper, we consider the nonparametric Bayesian approach to the multiple comparisons problem for I Poisson populations using Dirichlet process priors. We describe Gibbs sampling algorithm for calculating posterior probabilities for the hypotheses and calculate posterior probabilities for the hypotheses using Markov chain Monte Carlo. Also we provide a numerical example to illustrate the developed numerical technique.

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Semiparametric Inference for a Multistate Stochastic Survival Model

  • Sung Chil Yeo
    • Communications for Statistical Applications and Methods
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    • 제5권1호
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    • pp.239-263
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    • 1998
  • In this paper, we consider a multistate survival model which incorporates covariates and contains two illness states and two death states. The underlying stochastic process is assumed to follow nonhomogeneous Markov process. The estimates of survival, transition and competing risks probabilities are given via the methods of partial likelihood and nonparametric maximum likelihood. Our discussion is based on the statistical theory of counting process. An illustration is given to the data of patients in a heart transplant program. The goodness of fit procedures are also discussed to check the adequacy of the model.

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A Bayesian analysis based on beta-mixtures for software reliability models

  • Nam Seungmin;Kim Kiwoong;Cho Sinsup;Yeo Inkwon
    • 한국품질경영학회:학술대회논문집
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    • 한국품질경영학회 2004년도 품질경영모델을 통한 가치 창출
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    • pp.430-435
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    • 2004
  • Nonhomogeneous Poisson Process is often used to model failure times which occurred in software reliability and hardware reliability models. It can be characterized by its intensity functions or mean value functions. Many parametric intensity models have been proposed to account for the failure mechanism in real situation. In this paper, we propose a Bayesian semiparametric approach based on beta-mixtures. Two real datasets are analyzed.

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Survival Function Estimation for the Proportional Hazards Regression Model

  • Cha, Young Joon
    • 품질경영학회지
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    • 제18권1호
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    • pp.9-20
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    • 1990
  • The purpose of this paper is to propose the modified semiparametric estimators for survival function in the Cox's regression model with randomly censored data based on Tsiatis and Breslow estimators, and present their asymptotic variances estimates. The proposed estimators are compared to Tsiatis, Breslow, and Kaplan-Meier estimators through a small-sample Monte Carlo study. The simulation results show that the proposed estimators are preferred for small sample sizes.

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On Profile Likelihood for Gamma Frailty Models

  • Ha, Il-Do
    • Journal of the Korean Data and Information Science Society
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    • 제17권3호
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    • pp.999-1007
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    • 2006
  • The semiparametric gamma frailty models have been often used for multivariate survival analysis because they give an explicit marginal likelihood. The commonly used estimation procedure is the profile likelihood method based on marginal likelihood, which provides the same parameter estimates as the EM algorithm. In this paper we show in finite samples the standard profile-likelihood method can lead to an underestimation of parameters, particularly for the frailty parameter. To overcome this problem, we propose an adjusted profile-likelihood method. For the illustration a numerical example and a small-sample simulation study are presented.

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Semiparametric accelerated failure time model for the analysis of right censored data

  • Jin, Zhezhen
    • Communications for Statistical Applications and Methods
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    • 제23권6호
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    • pp.467-478
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    • 2016
  • The accelerated failure time model or accelerated life model relates the logarithm of the failure time linearly to the covariates. The parameters in the model provides a direct interpretation. In this paper, we review some newly developed practically useful estimation and inference methods for the model in the analysis of right censored data.

기후변화에 따른 농업생산성 변화의 일반균형효과 분석 (Climate Change, Agricultural Productivity, and their General Equilibrium Impacts: A Recursive Dynamic CGE Analysis)

  • 권오상;이한빈
    • 자원ㆍ환경경제연구
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    • 제21권4호
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    • pp.947-980
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    • 2012
  • 본고는 농업부문 및 국가경제에 대한 기후변화의 장기적 영향을 분석한다. 우선 작물 시뮬레이션 및 준모수적 분석법 등을 이용하여 쌀, 낙농 및 축산업에 대한 기후변화의 생산성 영향을 예측하고, 다음으로 축차적 동태 CGE모형을 이용하여 예측된 생산성 영향으로 유발되는 경제적 영향을 평가한다. 분석결과 우선 기후변화의 생산성 영향에서, 낙농 및 축산업의 경우 지속적으로 생산성이 하락하는 것으로 예측되었고, 쌀의 경우, 작물 시뮬레이션 적용 시 생산성 하락이, 준모수적 분석법을 적용 시 생산성이 상승한 후 다시 하락하는 것으로 예측되었다. 다음으로 쌀의 두 가지 예측결과를 기준으로 두 가지 시나리오를 설정하고 축차적 동태 CGE모형에 반영하여 경제적 영향을 평가한 결과, 2050년 연간 GDP 예상손실률이 시나리오에 따라 각각 0.2%, 0.02%로 나타났으며, 세부부문별로는 농업생산부문과 식품가공업, 농업용 투입재 산업, 그리고 몇몇 유통관련 산업에서 경제적 효과가 크게 나타났다. 그리고 대부분의 선행연구에서 간과되던 낙농 및 축산업 부문의 경제에 미치는 영향이 큰 것으로 나타났는데, 위 결과는 쌀부문 외 다른 농업생산부문에서의 기후변화 효과분석이 필요함을 제시한다.

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단일지표모형에서 계수 추정방법의 비교 (A comparison on coefficient estimation methods in single index models)

  • 최영웅;강기훈
    • Journal of the Korean Data and Information Science Society
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    • 제21권6호
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    • pp.1171-1180
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    • 2010
  • 회귀함수의 비모수적 적합에서 공변량의 차원이 증가함에 따라 추정량의 극한성질이 좋지 않음이 잘 알려져 있다. 이러한 문제점을 극복하기 위한 방법중의 하나는 단일지표모형의 추정을 이용하여 공변량의 차원을 1차원으로 줄이는 것이다. 단일지표모형에서 계수 추정 방법으로는 반복적으로 해를 계산하여 근사치를 구하는 방법인 준모수적 최소제곱법과 비반복적으로 계산하여 구하는 도함수 가중평균법이 있다. 두 추정 방법 모두 모수적인 방법과 같은 수렴비율로 정규근사한다고 알려져 있지만 실질적인 성능에 관한 비교는 이루어지지 않았다. 본 논문에서는 모의실험을 통해 두 방법에 의한 추정치의 분산을 비교하여 어떠한 방법이 좋은지를 파악하고자 한다.