• 제목/요약/키워드: Variance estimation

검색결과 734건 처리시간 0.027초

최소분산 자기동조 PID제어기 (A self tuning PID controller with minimum variance)

  • 조원철;전기준
    • 제어로봇시스템학회논문지
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    • 제2권1호
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    • pp.14-20
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    • 1996
  • This paper presents a self tuning method of a velocity type PID controller for minimum or non-minimum phase systems with time delays. The velocity type PID control structure is determined in the process of minimizing the variance of the auxilliary output, and self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a design parameter. This method is simple and effective compared with other existing methods[1,2]. Numerical examples are included to illustrate the procedure and to show the performance of the control system.

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Alternative Confidence Intervals on the Sum of Variance Components in a Simple Regression Model with Unbalanced Nested Error Structure

  • Park Dong Joon;Lee Soo Jin
    • Communications for Statistical Applications and Methods
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    • 제12권1호
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    • pp.87-100
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    • 2005
  • In order to construct confidence intervals on the sum of variance components in a simple regression model with unbalanced nested error structure, alternative confidence intervals using Graybill and Wang(1980) and generalized inference concept introduced by Tsui and Weerahandi(1989) are proposed. Computer simulation programmed by SAS/IML is performed to compare the simulated confidence coefficients and average interval lengths of the proposed confidence intervals. A numerical example is provided to demonstrate the confidence intervals and to show consistency between the example and simulation results.

A SIMPLE VARIANCE ESTIMATOR IN NONPARAMETRIC REGRESSION MODELS WITH MULTIVARIATE PREDICTORS

  • Lee Young-Kyung;Kim Tae-Yoon;Park Byeong-U.
    • Journal of the Korean Statistical Society
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    • 제35권1호
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    • pp.105-114
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    • 2006
  • In this paper we propose a simple and computationally attractive difference-based variance estimator in nonparametric regression models with multivariate predictors. We show that the estimator achieves $n^{-1/2}$ rate of convergence for regression functions with only a first derivative when d, the dimension of the predictor, is less than or equal to 4. When d > 4, the rate turns out to be $n^{-4/(d+4)}$ under the first derivative condition for the regression functions. A numerical study suggests that the proposed estimator has a good finite sample performance.

Optimum seat design for the quadruple offset butterfly valve by analysis of variance with orthogonal array

  • Lee, Sang-Beom;Lee, Dong-Myung
    • Journal of Advanced Marine Engineering and Technology
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    • 제38권8호
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    • pp.961-967
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    • 2014
  • In onshore and offshore plant engineering, a broad use of pipe system have been achieved and accordingly related technologies has been developed especially in the field of flow control valves. The aim of this study is to suggest the quadruple offset butterfly valve for bi-directional applications which show equivalent operating torque characteristics of the triple offset butterfly valve. Seat design parameters for the quadruple offset butterfly valve are determined by the proposed method utilizing both ANOVA (analysis of variance) and the orthogonal array. Through additive model considering the effect of design parameters on seating torque, mean estimation is performed and thus its optimization results are verified by design of experiment results. The insight obtained from the present study is beneficial for valve design engineers to develop reliable and integrated design of the quadruple offset butterfly valve.

On the Negative Estimates of Direct and Maternal Genetic Correlation - A Review

  • Lee, C.
    • Asian-Australasian Journal of Animal Sciences
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    • 제15권8호
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    • pp.1222-1226
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    • 2002
  • Estimates of genetic correlation between direct and maternal effects for weaning weight of beef cattle are often negative in field data. The biological existence of this genetic antagonism has been the point at issue. Some researchers perceived such negative estimate to be an artifact from poor modeling. Recent studies on sources affecting the genetic correlation estimates are reviewed in this article. They focus on heterogeneity of the correlation by sex, selection bias caused from selective reporting, selection bias caused from splitting data by sex, sire by year interaction variance, and sire misidentification and inbreeding depression as factors contributing sire by year interaction variance. A biological justification of the genetic antagonism is also discussed. It is proposed to include the direct-maternal genetic covariance in the analytical models.

BAYESIAN MODEL AVERAGING FOR HETEROGENEOUS FRAILTY

  • Chang, Il-Sung;Lim, Jo-Han
    • Journal of the Korean Statistical Society
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    • 제36권1호
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    • pp.129-148
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    • 2007
  • Frailty estimates from the proportional hazards frailty model often lead us to conjecture the heterogeneity in frailty such that the variance of the frailty varies over different covariate groups (e.g. male group versus female group). For such systematic heterogeneity in frailty, we consider a regression model for the variance components in the proportional hazards frailty model, denoted by the MLFM. However, in many cases, the observed data do not show any statistically significant preference between the homogeneous frailty model and the heterogeneous frailty model. In this paper, we propose a Bayesian model averaging procedure with the reversible jump Markov chain Monte Carlo which selects the appropriate model automatically. The resulting regression coefficient estimate ignores the model uncertainty from the frailty distribution in view of Bayesian model averaging (Hoeting et al., 1999). Finally, the proposed model and the estimation procedure are illustrated through the analysis of the kidney infection data in McGilchrist and Aisbett (1991) and a simulation study is implemented.

수문자료 확충을 위한 다중상관계수의 한계최소치 유도 (Derivation of the Critical Minimum Values of the Multiple Correlation Coefficient for Augmenting Hydrologic Samples)

  • 허준행
    • 물과 미래
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    • 제27권1호
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    • pp.133-140
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    • 1994
  • 주변 관측지점의 자료가 유용한 경우 관측자료가 짧은 지점의 평균과 분산 추정치를 개선하기 위하여 상관계수를 이용한 수문자료 확충을 이용하여왔다. 본 연구에서는 관측지점의 분산 추정치를 개선하기 위한 다중 상관계수의 한계최소치를 얻기 위하여, 다변량 정규분포에 근거하여 Moran이 유도한 확충자료 분산( ${{\sigma}_v}^2$ )의 불편 최우도추정량의 분산식을 Matalas와 Jacobs가 2변량 정규분포에 근거하여 유도한 식의 형태로 변형하였으며, 다양한 자료수와 지점수에 따라 다중상관계수의 한계최소치를 도표화했다.

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Merging Two Regional Geoid Estimates by Using Optimal Variance Components of Type repro-BIQUUE: An Algorithmic Approach

  • SCHAFFRIN Burkhard;MAUTZ Rainer
    • Korean Journal of Geomatics
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    • 제5권1호
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    • pp.1-6
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    • 2005
  • When merging various datasets the perennial problem of relative weighting arises. In case of two datasets an iterative algorithm has been developed recently that allows the rigorous determination of optimal variance components of type repro-BIQUUE even for large amounts of data, along with the estimation of the joint parameters. Here we shall present this new algorithm, and show its versatility in an example that will entail the merging of two regional geoid estimates (derived from EGM 96 and CHAMP) in terms of certain series expansions which have been proven previously to belong to the most efficient ones (e.g., wavelets, Hardy's multi-quadrics, etc.). Future attempts will be devoted to the sequential merging of altimeter and tide gauge data.

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고주파 과도신호의 파라미터 추정을 위한 칼만 필터링 기법에 관한 연구 (A Kalman Filtering Method for Estimation of Parameters of High Frequency Trans)

  • 이태훈;박진배;윤태성;고재원
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 하계학술대회 논문집 B
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    • pp.620-622
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    • 1998
  • This paper presents a method for estimating parameters of high frequency transient signals when noise is added. The parameters to be estimated are the magnitude, frequency, and decay rate of the signals. An approach based on only the extended Kalman filter (EKF) is highly dependent on choosing a correct value of variance of noise. The proposed method adopts an adaptive Kalman filter (AKF). Having very little information of the noise, This method avoids deterioration of the filter performance caused by choosing an inaccurate variance of the noise. The dependence of the EKF method upon the noise variance and the efficiency of the AKF method are shown.

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Performance of Spiked Population Models for Spectrum Sensing

  • Le, Tan-Thanh;Kong, Hyung-Yun
    • Journal of electromagnetic engineering and science
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    • 제12권3호
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    • pp.203-209
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    • 2012
  • In order to improve sensing performance when the noise variance is not known, this paper considers a so-called blind spectrum sensing technique that is based on eigenvalue models. In this paper, we employed the spiked population models in order to identify the miss detection probability. At first, we try to estimate the unknown noise variance based on the blind measurements at a secondary location. We then investigate the performance of detection, in terms of both theoretical and empirical aspects, after applying this estimated noise variance result. In addition, we study the effects of the number of SUs and the number of samples on the spectrum sensing performance.