• Communications for Statistical Applications and Methods
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• 제28권6호
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• pp.627-641
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• 2021

An asymmetric least squares estimation method has been employed to estimate linear models for percentile regression. An asymmetric maximum likelihood estimation (AMLE) has been developed for the estimation of Poisson percentile linear models. In this study, we propose generalized nonlinear percentile regression using the AMLE, and the use of the parametric bootstrap method to obtain confidence intervals for the estimates of parameters of interest and smoothing functions of estimates. We consider three conditional distributions of response variables given covariates such as normal, exponential, and Poisson for three mean functions with one linear and two nonlinear models in the simulation studies. The proposed method provides reasonable estimates and confidence interval estimates of parameters, and comparable Monte Carlo asymptotic performance along with the sample size and quantiles. We illustrate applications of the proposed method using real-life data from chemical and radiation epidemiological studies.

• 응용통계연구
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• 제31권1호
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• pp.123-137
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• 2018

비선형 혼합효과 모형은 다양한 분야에서 반복 측정 자료를 분석할 때 주로 사용된다. 비선형 혼합효과 모형은 개체 내 변동(intra-individual variation)에 대해 고려하는 제 1단계 개별수준모델(individual-level model)과 개체간 변동(inter-individual variation)에 대해 고려하는 제 2단계 개체군모델(population model)의 두 단계로 구성되어 있다. 비선형 혼합효과 모형의 첫 번째 단계인 개별수준모델은 비선형 회귀모형의 모수를 추정하는 것으로 일반적인 비선형 회귀모형과 같고, 주로 보통최소제곱추정 방법을 사용하여 모수를 추정한다. 그러나 최소제곱추정방법은 가정된 비선형 함수가 자료에 의해 명시적으로 드러나지 않는 경우 모수의 추정값과 그 표준오차가 극단적으로 커지는 문제가 발생할 수 있다. 본 논문에서는 최근에 비선형 회귀모형에서 제안된 능형회귀(ridge regression) 방법을 비선형 혼합효과 모형의 제 1단계 개별수준모델에 도입함으로써 이러한 문제를 해결할 수 있는 새로운 추정방법을 제안하였다. 제안된 추정량은 모의실험 연구를 통하여 기존의 표준적인 추정량과 그 성능을 비교하였다. 또한 미국의 National Toxicology Program으로부터 얻어진 정량적 대량고속 스크리닝(quantitative high throughput screening) 실제 자료를 사용하여 추정 방법들을 비교하였다.

• Genomics & Informatics
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• 제1권2호
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• pp.94-100
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• 2003

Motivation: Many have observed a nonlinear relationship between the signal intensity and the transcript abundance in microarray data. The first step in analyzing the data is to normalize it properly, and this should include a correction for the nonlinearity. The commonly used linear normalization schemes do not address this problem. Results: Nonlinearity is present in both cDNA and oligonucleotide arrays, but we concentrate on the latter in this paper. Across a set of chips, we identify those genes whose within-chip ranks are relatively constant compared to other genes of similar intensity. For each gene, we compute the sum of the squares of the differences in its within-chip ranks between every pair of chips as our statistic and we select a small fraction of the genes with the minimal changes in ranks at each intensity level. These genes are most likely to be non-differentially expressed and are subsequently used in the normalization procedure. This method is a generalization of the rank-invariant normalization (Li and Wong, 2001), using all available chips rather than two at a time to gather more information, while using the chip that is least likely to be affected by nonlinear effects as the reference chip. The assumption in our method is that there are at least a small number of non­differentially expressed genes across the intensity range. The normalized expression values can be substantially different from the unnormalized values and may result in altered down-stream analysis.

• Journal of the Korean Data and Information Science Society
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• 제20권4호
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• pp.749-755
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• 2009

Support vector classification (SVC) provides more complete description of the lin-ear and nonlinear relationships between input vectors and classifiers. In this paper. we propose the sparse kernel classifier to solve the optimization problem of classification with a modified hinge loss function and absolute loss function, which provides the efficient computation and the sparsity. We also introduce the generalized cross validation function to select the hyper-parameters which affects the classification performance of the proposed method. Experimental results are then presented which illustrate the performance of the proposed procedure for classification.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.445-456
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• 2003

Spatial data are usually obtained at selected locations even though they are potentially available at all locations in a continuous region. Moreover the monitoring locations are clustered in some regions, sparse in other regions. One important goal of spatial data analysis is to predict unknown response values at any location throughout a region of interest. Thus, an appropriate space model should be set up and their estimates and predictions must be accompanied by measures of uncertainty. In this study we see that a space model proposed allows a best interpolation to annual rainfall data in South Korea.

• Journal of the Korean Statistical Society
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• 제30권1호
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• pp.31-39
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• 2001

For estimating parameters of possibly nonlinear and/or non-stationary seasonal autoregressive(AR) processes, we introduce a new instrumental variable method which use the direction vector of the regressors in the same period as an instrument. On the basis of the new estimator, we propose new seasonal random walk tests whose limiting null distributions are standard normal regardless of the period of seasonality and types of mean adjustments. Monte-Carlo simulation shows that he powers of he proposed tests are better than those of the tests based on ordinary least squares estimator(OLSE).

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.872-877
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• 1990

Robustness of a model refernece direct adaptive pole placement control for not necessarily minimum phase systems is studied subject to unmodeled dynamics and bounded disturbances. The adaptive control scheme involves two estimators for the system and the controller parameter estimation, respectively. The robustness is obtaind under some weak assumptions and by using both a normalized least-squares algorithm with dead zone and an appropriate nonlinear feedback.

• 지질공학
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• 제19권1호
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• pp.71-79
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• 2009

다공질매질에 굴착된 2개의 관정과 단열암반층에 굴착된 2개의 관정으로 부터 단계양수시험이 실시되었다. Jacob(1947)이 제시한 P = 2.0 값은 단계양수시험의 수위강하를 해석하기 위하여 다공질매질과 단열암반층에 모두 적용되고 있다. 단계양수시험 해석에 대한 선형 모델(Jacob's graphic method)의 문제점들을 파악하기 위하여, 선형과 비선형 모델(Labadie and Helweg's least-sauares method)에서 산정된 우물상수(대수층손실상수(B), 우물손실상수(C) 및 우물손실지수(P))를 비교 분석하였다. 선형과 비선형 모델에서 산정된 C와 P값의 차이는 대수층의 투수성과 관정의 조건에 따라 다양하게 나타났다. 즉, 다공질매질에서 비선형 모델로 산정된 C값은 선형 모델로 산정된 C값에 비해 약 $10^0{\sim}10^{-2}$, 단열암반층에서는 약 $10^{-3}{\sim}10^{-6}$배 낮게 나타났다. 비선형 모델을 통해 산정된 다공질매질의 P값은 $2.124{\sim}2.775$, 단열암반층은 $3.459{\sim}5.635$의 범위로 산정되었으며, 이때 비선형 모델에서 우물손실은 P값에 따라 크게 좌우되었다. 선형과 비선형 모델을 통해 산정된 우물효율성의 차이는 다공질매질에서 $1.56{\sim}14.89%$, 단열암반층에서 $8.73{\sim}24.71%$를 보여 모델의 선택에 따라 상당한 오차를 가지는 것으로 나타났다. 또한 비선형의 최소제곱법을 적용한 회귀분석 방법이 모든 대수층의 단계양수시험 해석에 있어 매우 유용함을 확인하였다.

• Structural Engineering and Mechanics
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• 제24권1호
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• pp.31-50
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• 2006

This paper deals with the mechanical behaviour of the thin-walled cylindrical air-spring shell (CAS) made of rubber-textile cord composite (RCC) subjected to different types of loading. An orthotropic hyperelastic constitutive model is presented which can be applied to numerical simulation for the response of biological soft tissue and of the nonlinear anisotropic hyperelastic material of the CAS used in vibroisolation of driver's seat. The parameters of strain energy function of the constitutive model are fitted to the experimental results by the nonlinear least squares method. The deformation of the inflated CAS is calculated by solving the system of five first-order ordinary differential equations with the material constitutive law and proper boundary conditions. Nonlinear hyperelastic constitutive equations of orthotropic composite material are incorporated into the finite strain analysis by finite element method (FEM). The results for the deformation analysis of the inflated CAS made of RCC are given. Numerical results of principal stretches and deformed profiles of the inflated CAS obtained by numerical deformation analysis are compared with experimental ones.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1998년도 봄 학술발표회 논문집(I)
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• pp.347-352
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• 1998

The purpose of this paper is to present and establish a procedure to predict the prestress forces during the service life of the structure. The statistical approach of this procedure is using the in-situ measurement data of the post-tensioning system to develop a nonlinear regression analysis. The method of least squares is used to fit a certain function a set of data. Use of a nonlinear model is achieved by its logarithmic transformation and sunsequent use of linear-regression theory. The regression analysis result can be used to check the prestress force during the service life so that the remaining prestress force is equal to or exceeds the design requirement. Results from the measurement data of PSC box girder bridge structure were used to demonstrate the procedures.