• Journal of the Korean Data and Information Science Society
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• 제23권2호
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• pp.385-392
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• 2012

Logistic regression is a well known binary classification method in the field of statistical learning. Mixed-effect regression models are widely used for the analysis of correlated data such as those found in longitudinal studies. We consider kernel extensions with semiparametric fixed effects and parametric random effects for the logistic regression. The estimation is performed through the penalized likelihood method based on kernel trick, and our focus is on the efficient computation and the effective hyperparameter selection. For the selection of optimal hyperparameters, cross-validation techniques are employed. Numerical results are then presented to indicate the performance of the proposed procedure.

• Journal of the Korean Statistical Society
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• 제32권1호
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• pp.85-92
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• 2003

We consider the partially linear model E(Y) : X$^{t}$ $\beta$＋η(Z) when the X's are measured with additive error. The semiparametric likelihood estimation ignoring the measurement error gives inconsistent estimator for both $\beta$ and η(.). In this paper we suggest the SIMEX estimator for f to correct the bias induced by measurement error, and explore its properties. We show that the rational linear extrapolant is proper in extrapolation step in the sense that the SIMEX method under this extrapolant gives consistent estimator It is also shown that the SIMEX estimator is asymptotically equivalent to the semiparametric version of the usual parametric correction for attenuation suggested by Liang et al. (1999) A simulation study is given to compare two variance estimating methods for SIMEX estimator.

• 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.

• 응용통계연구
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• 제36권4호
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• pp.323-335
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• 2023

고차원 데이터의 인과 추론에서 고차원 공변량의 차원을 축소하고 적절히 변형하여 처리와 잠재 결과에 영향을 줄 수 있는 교란을 통제하는 것은 중요한 문제이다. 평균 처리 효과(average treatment effect; ATE) 추정에 있어서, 성향점수와 결과 모형 추정을 이용한 확장된 역확률 가중치 방법이 주로 사용된다. 고차원 데이터의 분석시 모든 공변량을 포함한 모수 모형을 이용하여 성향 점수와 결과 모형 추정을 할 경우, ATE 추정량이 일치성을 갖지 않거나 추정량의 분산이 큰 값을 가질 수 있다. 이런 이유로 고차원 데이터에 대한 적절한 차원 축소 방법과 준모수 모형을 이용한 ATE 방법이 주목 받고 있다. 이와 관련된 연구로는 차원 축소부분에 준모수 모형과 희소 충분 차원 축소 방법을 활용한 연구가 있다. 최근에는 성향점수와 결과 모형을 추정하지 않고, 차원 축소 후 매칭을 활용한 ATE 추정 방법도 제시되었다. 고차원 데이터의 ATE 추정 방법연구 중 최근에 제시된 네 가지 연구에 대해 소개하고, 추정치 해석시 유의할 점에 대하여 논하기로 한다.

• 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.

• 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.

• 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.

• 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.

• Communications for Statistical Applications and Methods
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• 제29권3호
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• pp.287-299
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• 2022

In radiation epidemiology, the excess relative risk (ERR) model is used to determine the dose-response relationship. In general, the dose-response relationship for the ERR model is assumed to be linear, linear-quadratic, linear-threshold, quadratic, and so on. However, since none of these functions dominate other functions for expressing the dose-response relationship, a Bayesian semiparametric method using splines has recently been proposed. Thus, we improve the Bayesian semiparametric method for the selection of the tuning parameters for splines as the number and location of knots using a Bayesian knot selection method. Equally spaced knots cannot capture the characteristic of radiation exposed dose distribution which is highly skewed in general. Therefore, we propose a nonparametric Bayesian knot selection method based on a Dirichlet process mixture model. Inference of the spline coefficients after obtaining the number and location of knots is performed in the Bayesian framework. We apply this approach to the life span study cohort data from the radiation effects research foundation in Japan, and the results illustrate that the proposed method provides competitive curve estimates for the dose-response curve and relatively stable credible intervals for the curve.

• 응용통계연구
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• 제25권5호
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• pp.707-718
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• 2012

We propose a semi-parametric model to analyze clustered and interval-censored data; in addition, we plugged-in a gamma frailty to the model to measure the association of members within the same cluster. We propose an estimation procedure based on EM algorithm. Simulation results showed that our estimation procedure may result in unbiased estimates. The standard error is smaller than expected and provides conservative results to estimate the coverage rate; however, this trend gradually disappeared as the number of members in the same cluster increased. In addition, our proposed method was illustrated with data taken from diabetic retinopathy studies to evaluate the effectiveness of laser photocoagulation in delaying or preventing the onset of blindness in individuals with diabetic retinopathy.