• 응용통계연구
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• 제25권5호
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• pp.793-802
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• 2012

One proposal is made to construct a nonparametric estimator of slope parameters in a regression model under symmetric error distributions. This estimator is based on the use of the idea of minimizing approximate variance of a proposed estimator using regression quantiles. This nonparametric estimator and some other L-estimators are studied and compared with well known M-estimators through a simulation study.

• Journal of the Korean Statistical Society
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• 제30권3호
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• pp.481-498
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• 2001

Empirical Bayes procedure of nonparametric estiamtion of cumulative hazard rates based on censored data is considered using the beta process priors of Hjort(1990). Beta process priors with unknown parameters are used for cumulative hazard rates. Empirical Bayes estimators are suggested and asymptotic optimality is proved. Our result generalizes that of Susarla and Van Ryzin(1978) in the sensor that (i) the cumulative hazard rate induced by a Dirichlet process is a beta process, (ii) our empirical Bayes estimator does not depend on the censoring distribution while that of Susarla and Van Ryzin(1978) does, (iii) a class of estimators of the hyperprameters is suggested in the prior distribution which is assumed known in advance in Susarla and Van Ryzin(1978). This extension makes the proposed empirical Bayes procedure more applicable to real dta sets.

• Communications for Statistical Applications and Methods
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• 제27권5호
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• pp.547-568
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• 2020

Modeling the statistical autocorrelations in spatial data is often achieved through the estimation of the variograms, where the selection of the appropriate valid variogram model, especially for small samples, is crucial for achieving precise spatial prediction results from kriging interpolations. To estimate such a variogram, we traditionally start by computing the empirical variogram (traditional Matheron or robust Cressie-Hawkins or kernel-based nonparametric approaches). In this article, we conduct numerical studies comparing the performance of these empirical variograms. In most situations, the nonparametric empirical variable nearest-neighbor (VNN) showed better performance than its competitors (Matheron, Cressie-Hawkins, and Nadaraya-Watson). The analysis of the spatial groundwater dataset used in this article suggests that the wave variogram model, with hole effect structure, fitted to the empirical VNN variogram is the most appropriate choice. This selected variogram is used with the ordinary kriging model to produce the predicted pollution map of the nitrate concentrations in groundwater dataset.

• International Journal of CAD/CAM
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• 제9권1호
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• pp.31-36
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• 2010

3D point data acquired from laser scan or stereo vision can be quite noisy. A preprocessing step is often needed before a surface reconstruction algorithm can be applied. In this paper, we propose a nonparametric approach for noisy point data preprocessing. In particular, we proposed an anisotropic kernel based nonparametric density estimation method for outlier removal, and a hill-climbing line search approach for projecting data points onto the real surface boundary. Our approach is simple, robust and efficient. We demonstrate our method on both real and synthetic point datasets.

• Journal of the Korean Data and Information Science Society
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• 제25권3호
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• pp.611-622
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• 2014

The inverse Weibull distribution (IWD) is the complementary Weibull distribution and plays an important role in many application areas. In Bayesian analysis, Soland's method can be considered to avoid computational complexities. One limitation of this approach is that parameters of interest are restricted to a finite number of values. This paper introduce nonparametric Bayesian estimator in the context of record statistics values from the exponentiated inverse Weibull distribution (EIWD). In stead of Soland's conjugate piror, stick-breaking prior is considered and the corresponding Bayesian estimators under the squared error loss function (quadratic loss) and LINEX loss function are obtained and compared with other estimators. The results may be of interest especially when only record values are stored.

• 한국멀티미디어학회논문지
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• 제17권2호
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• pp.200-207
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• 2014

Blood pressure (BP) is an important vital signal for determining the health of an individual subject. Although estimation of mean arterial blood pressure is possible using oscillometric blood pressure techniques, there are no established techniques in the literature for obtaining confidence interval (CI) for systolic blood pressure (SBP) and diastolic blood pressure (DBP) estimates obtained from such BP measurements. This paper proposes a nonparametric bootstrap technique to obtain CI with a small number of the BP measurements. The proposed algorithm uses pseudo measurements employing nonparametric bootstrap technique to derive the pseudo maximum amplitudes (PMA) and the pseudo envelopes (PE). The SBP and DBP are then derived using the new relationships between PMA and PE and the CIs for such estimates. Application of the proposed method on an experimental dataset of 85 patients with five sets of measurements for each patient has yielded a smaller Cl than the conventional student t-method.

• 응용통계연구
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• 제31권3호
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• pp.343-352
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• 2018

설명변수가 주어졌을 때 반응변수의 평균적인 추세뿐만 아니라 극단적인 지역에서의 추세에 대해서 추정하고 싶거나 반응변수 분포의 일반적인 탐색을 위해서는 분위수 회귀분석과 평률 회귀분석을 사용할 수 있다. 본 논문에서는 평률 회귀모형의 추정을 위한 모수적 방법과 비모수적 방법의 성능을 비교하고자 한다. 이를 위해 각 추정 방법을 소개하고 여러 상황의 모의실험 및 실제자료에의 적용을 통해 비교 분석을 실시하였다. 모형에 따라 성능 차이가 있는데 자료의 형태가 복잡하여 변수 간의 관계를 유추하기 힘들 경우 비모수적으로 추정한 평률 회귀분석모형이 더욱 좋은 결과를 보였다. 일반적인 회귀분석의 경우와 달리 평률의 경우 후보가 되는 모수 모형을 상정하기 어렵다는 측면에서 볼 때, 비모수적 방법의 사용이 추천될 수 있다.

• 응용통계연구
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• 제15권2호
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• pp.355-366
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• 2002

범주형 자료의 구조파악에 주로 이용되는 로짓모형에서 비모수적 방법을 이용한 모수의 신뢰구간추정과 가설검정 등의 통계적 추론에 대하여 살펴보았다. 모수에 대한 통계적 추론에서 정규분포에 근거한 모수적 방법(Wald 방법)보다는 붓스트랩 방법이나 임의순열을 활용한 비모수적 방법이 많이 활용되고 있다. 본 연구에서는 로짓모형의 모수에 대한 비모수적 추론방법으로 붓스트랩(bootstrap)과 임의순열(random permutation)의 두 방법을 고려하고 모의실험을 통하여 가설검정의 검정력과 신뢰구간추정의 포함확률을 비교하였고 사례분석을 다루었다.

• 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.

• Communications for Statistical Applications and Methods
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• 제7권1호
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• pp.129-140
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• 2000

Wavelets constitute a new orthogonal system which has direct application in density estimation. We introduce a brief wavelet density estimation and summarize some asymptotic results. An application to mixture normal distributions is implemented with S-Plus.