• Journal of the Korean Statistical Society
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• 제30권2호
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• pp.281-290
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• 2001

Symmetric estimation and recursive mean adjustment are considered to construct tests for the doble unit root hypothesis for both parametric and semiparametric time series models. It is shown that simultaneous application of symmetric estimation and recursive mean adjustment yields the most powerful test. Moreover, size property of the semiparametric test based on the simultaneous application is bet among all semiparametric tests.

• Communications for Statistical Applications and Methods
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• 제17권4호
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• pp.551-560
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• 2010

This paper considers a Bayesian approach to modeling a flexible regression function under structural measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under structural measurement error model without a semiparametric component.

• Journal of the Korean Data and Information Science Society
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• 제21권2호
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• pp.379-385
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• 2010

This paper considers Bayesian approach to modeling a flexible regression function under functional measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under functional measurement error model without semiparametric component.

• Journal of the Korean Data and Information Science Society
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• 제19권2호
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• pp.421-429
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• 2008

We consider a general semiparametric additive risk model that consists of three components. They are parametric, purely and smoothly nonparametric components. In parametric component, time dependent term is known up to proportional constant. In purely nonparametric component, time dependent term is an unknown function, and time dependent term in smoothly nonparametric component is an unknown but smoothly function. As an estimation method of this model, we use the weighted least square estimation by Huffer and McKeague (1991). We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least square method.

• Journal of the Korean Statistical Society
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• 제36권4호
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• pp.523-542
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• 2007

In this paper we consider semiparametric random effect panel models that contain AR(p) disturbances. We derive the efficient score function and the information bound for estimating the slope parameters. We make minimal assumptions on the distribution of the random errors, effects, and the regressors, and provide semiparametric efficient estimates of the slope parameters. The present paper extends the previous work of Park et al.(2003) where AR(1) errors were considered.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.209-216
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• 2003

Contingent valuation method (CVM) is a main evaluation method of nonmarket goods for which markets either do not exist at all or do exist only incompletely; an example is environmental good. A dichotomous choice approach, the most popular type of CVM in environmental economics, employs binary discrete choice models as statistical estimation models. In this paper, we propose a semiparametric dichotomous choice CVM method using local linear model of Fan and Gijbels (1996) in which probability distribution of error term is specified parametrically but latent structural function is specified nonparametrically. The computation procedures of the proposed method are illustrated with a simple design of simulations.

• 자원ㆍ환경경제연구
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• 제12권4호
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• pp.545-557
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• 2003

양분형 조건부가치평가모형의 준모수적 추정 방법을 소위 회귀함수 1차 도함수의 밀도가중평균(density weighted average derivative or regression function) 추정을 응용하여 제안한다. 논문에서 제안된 준모수 추정량의 소표본 특성은 몬데칼로 시뮬레이션 결과를 제시함으로써 간접적으로 나타난다. 또 추정량을 동강보존을 위한 지불용의액을 조사한 조건부가치평가자료에 실제 적용함으로써 현실 적용 가능성을 보여준다.

• 응용통계연구
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• 제27권4호
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• pp.605-617
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• 2014

소지역추정은 작은 규모의 지역 또는 도메인에 작은 크기의 표본이 배정되어 추정의 정도가 좋지 않은 경우에 이를 극복하는 통계적 기법이다. 소지역추정에 흔히 사용되고 있는 모형기반 추정량은 MSE를 기초로 얻어지나 최근 상대오차를 이용한 소지역추정법도 연구되고 있다. 본 논문에서는 상대오차를 최소로 하는 소지역 추정량의 준모수적 접근법에 관하여 연구하였다. 즉 준모수혼합모형을 이용한 축소소지역추정량을 새롭게 제안하였다. 또한 Lee(1995)에서 제안된 모의실험 자료를 이용한 모의실험과 매월노동통계 자료를 이용한 사례연구를 통하여 기존의 추정량과 제안된 추정량의 우수성을 비교하였다.

• 응용통계연구
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• 제26권1호
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• pp.71-79
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• 2013

지역 또는 도메인에 작은 크기의 표본이 배정되어 추정의 정도가 나쁜 경우에 사용되는 준모수적 또는 비모수적 소지역 추정법은 최근 많은 연구가 진행되고 있다. 본 논문에서는 커널을 이용한 국소다항 혼합모형 소지역 추정법과 벌점 스플라인을 이용한 혼합모형 소지역 추정법이 연구되었다. 이 두 방법과 소지역추정에 흔히 사용되고 있는 선형 혼합모형을 모의실험을 통해 그 우수성을 비교하였다.

• Journal of the Korean Data and Information Science Society
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• 제28권5호
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• pp.1191-1204
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• 2017

Weighted least squares (WLS) estimation is often easily used for the data with heteroscedastic errors because it is intuitive and computationally inexpensive. However, WLS estimator is less robust to a few outliers and sometimes it may be inefficient. In order to overcome robustness problems, Box-Cox transformation, Huber's M estimation, bisquare estimation, and Yohai's MM estimation have been proposed. Also, more efficient estimations than WLS have been suggested such as Bayesian methods (Cepeda and Achcar, 2009) and semiparametric methods (Kim and Ma, 2012) in heteroscedastic error models. Recently, Çelik (2015) proposed the weight methods applicable to the heteroscedasticity patterns including butterfly-distributed residuals and megaphone-shaped residuals. In this paper, we review heteroscedastic regression estimators related to robust or efficient estimation and describe their properties. Also, we analyze cost data of U.S. Electricity Producers in 1955 using the methods discussed in the paper.