• Journal of the Korean Statistical Society
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• 제33권4호
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• pp.401-410
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• 2004

We address the problem of parameter estimation in multivariate distributions under ignorable non-monotone missing data. The factoring likelihood method for monotone missing data, termed by Rubin (1974), is extended to a more general case of non-monotone missing data. The proposed method is algebraically equivalent to the Newton-Raphson method for the observed likelihood, but avoids the burden of computing the first and the second partial derivatives of the observed likelihood. Instead, the maximum likelihood estimates and their information matrices for each partition of the data set are computed separately and combined naturally using the generalized least squares method.

• Journal of the Korean Data and Information Science Society
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• 제10권1호
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• pp.207-214
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• 1999

Optimal estimating functions for a class of autoregressive models with GARCH(1,1) error are discussed. The asymptotic properties of the estimator as the solution of the optimal estimating equation are investigated for the models. We have also some simulation results which suggest that the proposed optimal estimators have smaller sample variances than those of the Conditional least-squares estimators under the heavy-tailed error distributions.

• Journal of the Korean Data and Information Science Society
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• 제15권2호
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• pp.307-316
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• 2004

Principal Component Regression(PCR) and Partial Least Squares Regression(PLSR) are the two most popular regression techniques in chemometrics. In the field of chemometrics usually the number of regressor variables greatly exceeds the number of observation. So we have to reduce the number of regressors to avoid the identifiability problem. In this paper we compare PCR and PLSR techniques combined with various robust regression methods including regression depth estimation. We compare the efficiency, goodness-of-fit and robustness of each estimators under several contamination schemes.

• 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.

• 한국음향학회지
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• 제39권1호
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• pp.32-37
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• 2020

본 논문은 l₁놈-Recursive Least Squares(RLS)에 수치 계산상 견실화를 더한 새로운 알고리즘을 제안한다. Eksioglu와 Tanc는 희소성 음향 채널 추정을 위해서 l₁놈-RLS 알고리즘을 구현하였다. 그러나 이 알고리즘의 근간인 RLS 계산법 역행렬 계산에서 수치 계산상의 불안정성을 지니고 있다. 본 논문에서는 이런 불안정성을 낮추는 새로운 알고리즘을 제안한다. 그리고 제안한 방법을 사용했을 때 수치적 불안정성에 대한 성능이 개선되었음을 보인다.

• 한국정보처리학회논문지
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• 제5권9호
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• pp.2345-2352
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• 1998

최근에 개발되어 성공적으로 적용되고 있는 초기하분포 소프트웨어 신뢰성 성장 모델의 모수는 최우추정법으로 추정하기가 쉽지 않으므로주로 최소자승법으로 추정하고 있다. 본 논문에서는 먼저 기존의 최소자승법에서 사용된 최소화 기준을 비교한 다음, 새로 발견되는 결함수의 분산이 일정하지 않음을 고려한 가중최소자승법을 제안한다. 그리고 두 개의 실제 자료를 분석하여 가중최소자승법이 적합함을 보인다. 마지막으로 임의의 테스팅 시점에서 추가 시험에 의해 발견된 새로운 결함수를 예측하는 방법을 제안한다. 이 예측 방법은 테스팅을 중단하는 시점을 결정할 때 이용될 수 있을 것이다.

• 한국음향학회지
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• 제23권5호
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• pp.370-375
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• 2004

본 논문에서는, 미지 위치의 원거리 능동음원을 이용하여 해저고정형 선배열 센서에 대한 3차원 배열형상추정 기법을 제안하였다. 본 연구는 센서에 도달하는 음파가 평면파라는 가정 하에 기준센서와 나머지 센서간의 음파도달 시간지연, 센서위치 및 입사각과의 선형방정식의 해를 반복적 최소자승법에 의해 구함으로서 센서위치 추정이 가능하다. 제안된 기법의 타당성을 검증하기 위해 컴퓨터 시뮬레이션과 실제 해상실험을 수행하였으며, 이론적 분석을 통하여 음원 위치 분포에 따른 성능 및 시간지연 오차에 따른 센서위치 추정 성능을 분석하였다.

• 한국음향학회지
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• 제35권5호
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• pp.383-388
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• 2016

본 논문은 볼록 규준화 RLS(Recursive Least Squares)에 쓰이는 규준화를 위한 상수를 정하는 법을 제안한다. Eksioglu와 Tanc는 희소성 음향 채널 추정을 위해서 볼록 규준화 RLS 알고리즘을 구현하였다. 그러나 이 알고리즘은 더 좋은 추정 성능을 위해서 채널의 참 임펄스 응답 정보가 사용된다. 본 논문에서는 이 같은 참 임펄스 응답 정보가 필요 없는 규준화 상수를 위한 두 가지 선정법을 제안한다. 그리고 제안한 방법을 사용했을 때 Eksioglu와 Tanc의 방법에 필적한 추정 성능을 유지함을 보인다.

• Journal of Sport and Applied Science
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• 제2권2호
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• pp.1-10
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• 2018

Prior literature has posited that the sport industry has been effective method to drive the economic growth. Given the rationale, this study sets China as a research object with a quarterly data from the first quarter of 2003 to the fourth quarter of 2017 to explore how the sport industry affects economic growth. This study employed Johansen cointegration test and dynamic ordinary least squares as methods for an empirical analysis. The input of sport industry, the labor input, the capital input, and the economic growth are used as research variables. The results show that there is a long-run relationship among them. Johansen cointegration test's estimation indicated that 1% increase in the input of sport industry will lead to 0.064% increase in economic growth. Dynamic ordinary least squares' estimation showed that whenever in the one lead, in the one lag and in the present period, the input of sport industry always poses a positive effect on economic growth. Labor input also has a positive effect on economic growth. The capital input has a negative effect on economic growth. Finally, even though the input of sport industry has a positive effect on economic growth, its impact on economic growth is relative weak.

• Smart Structures and Systems
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• 제14권6호
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• pp.1247-1267
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• 2014

Real-Time Hybrid Simulation (RTHS) is a novel approach conceived to evaluate dynamic responses of structures with parts of a structure physically tested and the remainder parts numerically modelled. In RTHS, delay estimation is often a precondition of compensation; nonetheless, system delay may vary during testing. Consequently, it is sometimes necessary to measure delay online. Along these lines, this paper proposes an online delay estimation method using least-squares algorithm based on a simplified physical system model, i.e., a pure delay multiplied by a gain reflecting amplitude errors of physical system control. Advantages and disadvantages of different delay estimation methods based on this simplified model are firstly discussed. Subsequently, it introduces the least-squares algorithm in order to render the estimator based on Taylor series more practical yet effective. As a result, relevant parameter choice results to be quite easy. Finally in order to verify performance of the proposed method, numerical simulations and RTHS with a buckling-restrained brace specimen are carried out. Relevant results show that the proposed technique is endowed with good convergence speed and accuracy, even when measurement noises and amplitude errors of actuator control are present.