• Title/Summary/Keyword: General linear model

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The General Linear Test in the Ridge Regression

  • Bae, Whasoo;Kim, Minji;Kim, Choongrak
    • Communications for Statistical Applications and Methods
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    • v.21 no.4
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    • pp.297-307
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    • 2014
  • We derive a test statistic for the general linear test in the ridge regression model. The exact distribution for the test statistic is too difficult to derive; therefore, we suggest an approximate reference distribution. We use numerical studies to verify that the suggested distribution for the test statistic is appropriate. A asymptotic result for the test statistic also is considered.

Robust $H_{\infty}$ Control for Uncertain Two-Dimensional Discrete Systems Described by the General Model via Output Feedback Controllers

  • Xu, Huiling;Zou, Yun;Xu, Shengyuan;Guo, Lei
    • International Journal of Control, Automation, and Systems
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    • v.6 no.5
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    • pp.785-791
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    • 2008
  • This paper considers the problem of robust $H_{\infty}$ control for uncertain 2-D discrete systems in the General Model via output feedback controllers. The parameter uncertainty is assumed to be norm-bounded. The purpose is the design of output feedback controllers such that the closed-loop system is stable while satisfying a prescribed $H_{\infty}$ performance level. In terms of a linear matrix inequality, a sufficient condition for the solvability of the problem is obtained, and an explicit expression of desired output feedback controllers is given. An example is provided to demonstrate the application of the proposed method.

Bayesian Hypothesis Testing in Multivariate Growth Curve Model.

  • Kim, Hea-Jung;Lee, Seung-Joo
    • Journal of the Korean Statistical Society
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    • v.25 no.1
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    • pp.81-94
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    • 1996
  • This paper suggests a new criterion for testing the general linear hypothesis about coefficients in multivariate growth curve model. It is developed from a Bayesian point of view using the highest posterior density region methodology. Likelihood ratio test criterion(LRTC) by Khatri(1966) results as an approximate special case. It is shown that under the simple case of vague prior distribution for the multivariate normal parameters a LRTC-like criterion results; but the degrees of freedom are lower, so the suggested test criterion yields more conservative test than is warranted by the classical LRTC, a result analogous to that of Berger and Sellke(1987). Moreover, more general(non-vague) prior distributions will generate a richer class of tests than were previously available.

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A Yield Estimation Model of Forage Rye Based on Climate Data by Locations in South Korea Using General Linear Model

  • Peng, Jing Lun;Kim, Moon Ju;Kim, Byong Wan;Sung, Kyung Il
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.36 no.3
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    • pp.205-214
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    • 2016
  • The objective of this study was to construct a forage rye (FR) dry matter yield (DMY) estimation model based on climate data by locations in South Korea. The data set (n = 549) during 29 years were used. Six optimal climatic variables were selected through stepwise multiple regression analysis with DMY as the response variable. Subsequently, via general linear model, the final model including the six climatic variables and cultivated locations as dummy variables was constructed as follows: DMY = 104.166SGD + 1.454AAT + 147.863MTJ + 59.183PAT150 - 4.693SRF + 45.106SRD - 5230.001 + Location, where SGD was spring growing days, AAT was autumnal accumulated temperature, MTJ was mean temperature in January, PAT150 was period to accumulated temperature 150, SRF was spring rainfall, and SRD was spring rainfall days. The model constructed in this research could explain 24.4 % of the variations in DMY of FR. The homoscedasticity and the assumption that the mean of the residuals were equal to zero was satisfied. The goodness-of-fit of the model was proper based on most scatters of the predicted DMY values fell within the 95% confidence interval.

IMC design for nonlinear plants using multiple models, controllers, and switching (다중 모델, 제어기, 스위칭을 이용한 비선형 플랜트의 IMC 제어기 설계)

  • 오원근;구세완;서병설
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.241-244
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    • 1996
  • This paper discusses the general properties and the design procedures of Internal Model Control(IMC) scheme for nonlinear plants. Also we propose new nonlinear IMC(NIMC) design method using linear IMC. Although all IMC controllers can be thought simple 'inverse controller', its nonlinear realization is not easy. Propose NIMC is composed multiple linear models, IMC controllers, and switching scheme. The advantages of this method are we can use simple linear IMC design method and need not nonlinear modelings.

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Optimal Pipe Replacement Analysis with a New Pipe Break Prediction Model (새로운 파괴예측 모델을 이용한 상수도 관의 최적 교체)

  • Park, Suwan;Loganathan, G.V.
    • Journal of Korean Society of Water and Wastewater
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    • v.16 no.6
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    • pp.710-716
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    • 2002
  • A General Pipe Break Prediction Model that incorporates linear and exponential models in its form is developed. The model is capable of fitting pipe break trends that have linear, exponential or in between of linear and exponential trend by using a weighting factor. The weighting factor is adjusted to obtain a best model that minimizes the sum of squared errors of the model. The model essentially plots a best curve (or a line) passing through "cumulative number of pipe breaks" versus "break times since installation of a pipe" data points. Therefore, it prevents over-predicting future number of pipe breaks compared to the conventional exponential model. The optimal replacement time equation is derived by using the Threshold Break Rate equation by Loganathan et al. (2002).

A Linear Filtering Method for Statistical Process Control with Autocorrelated Data (자기상관 데이터의 통계적 공정관리를 위한 선형 필터 기법)

  • Jin Chang-Ho;Apley Daniel W.
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.05a
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    • pp.92-100
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    • 2006
  • In many common control charting situations, the statistic to be charted can be viewed as the output of a linear filter applied to the sequence of process measurement data. In recent work that has generalized this concept, the charted statistic is the output of a general linear filter in impulse response form, and the filter is designed by selecting its impulse response coefficients in order to optimize its average run length performance. In this work, we restrict attention to the class of all second-order linear filters applied to the residuals of a time series model of the process data. We present an algorithm for optimizing the design of the second-order filter that is more computationally efficient and robust than the algorithm for optimizing the general linear filter. We demonstrate that the optimal second-order filter performs almost as well as the optimal general linear filter in many situations. Both methods share a number of interesting characteristics and are tuned to detect any distinct features of the process mean shift, as it manifests itself in the residuals.

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Simplified 3D Finite Element Analysis of Linear Inductor Motor for Integrated Magnetic Suspension/Propulsion Applications (자기부상 및 추진 일체형 리니어 인덕터 모터의 간이형 3차원 유한요소해석)

  • Jeong, Sang-Sub;Jang, Seok-Myeong
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.49 no.6
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    • pp.371-379
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    • 2000
  • The 4-pole linear homopolar synchronous motor (LHSM), so called linear inductor motor, is composed of the figure-of-eight shaped 3-phase armature windings, DC field windings, and the segmented secondary with the transverse bar track. To reduce the calculation time, the simplified 3D finite element model with equivalent reluctance and/or permanent magnet is presented. To obtain a clear understanding, propriety and usefulness of the developed model, we compare with the results of simplified 3D FEA, general 3D FEA and test. Consequently, the results of simplified and 3D FEM analysis are nearly identical, but much larger than that of static test at d-axis armature excitation. Therefore the improved FEA model, such as full model with half slot, is needed for the precise analysis.

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G-Inverse and SAS IML for Parameter Estimation in General Linear Model (선형 모형에서 모수 추정을 위한 일반화 역행렬 및 SAS IML 이론에 관한 연구)

  • Choi, Kuey-Chung;Kang, Kwan-Joong;Park, Byung-Jun
    • The Korean Journal of Applied Statistics
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    • v.20 no.2
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    • pp.373-385
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    • 2007
  • The solution of the normal equation arising in a general linear model by the least square methods is not unique in general. Conventionally, SAS IML and G-inverse matrices are considered for such problems. In this paper, we provide a systematic solution procedures for SAS IML.

Reduction of the Seismetic rRspocses by Using the Modified Hysteretic Bi-Linear Model of the Seismic Isolator (수정히스테리틱 Bi-Linear 면진베어린 모델을 사용한 지진응답감소)

  • Koo, G.H.;Lee, J.H.;Kim, J.B.;Lee, H.Y.;Yoo, B.
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.20 no.1
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    • pp.127-134
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    • 1996
  • In general, seismic isolators which are made of laminated rubber and shim plate have characteristics of complex hysteretic behavior. When shear deformation of the seismic isolator is small, the isolator hassimple hysteretic almost bi-linear behabior. But on large shear deformation hardening effects may occur. This paper proposes a moldeling method of the seimic isolator with modified hysteretic bi-linear model which can consider the hardening effects. From the results of the seismic analyses of the isolated system it is shown that the responses are singificantly reduced compared with those of the non-isolated system. The modified hysteretic bi-linear model of the isolator gives larger ZPA(zero period acceleration) than those of the simple hysteretic bi-linear model and the equivalunt spring-damper model.