• Title/Summary/Keyword: 오차제곱합

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Derivation of error sum of squares of two stage nested designs and its application (이단계 지분계획법의 오차제곱합 유도와 그 활용)

  • Kim, Daehak
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1439-1448
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    • 2013
  • The analysis of variance for randomized block design or two way classification data is well known. In this paper, particularly, we considered two stage nested design in which the levels of one factor is not identical for different levels of another factor. We investigate the structural properties of two stage nested design and the properties of error sum of squares for random effect model. For the application of two way nested design, we consider two-period crossover design which is used commonly for the equivalence test to bio-similar product. The confidence interval estimation of the difference of two population means in the crossover design is discussed based on statistical package SPSS.

Suppression for Logistic Regression Model (로지스틱 회귀모형에서의 SUPPRESSION)

  • Hong C. S.;Kim H. I.;Ham J. H.
    • The Korean Journal of Applied Statistics
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    • v.18 no.3
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    • pp.701-712
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    • 2005
  • The suppression for logistic regression models has been debated no longer than that for linear regression models since, among many other reasons, sum of squares for regression (SSR) or coefficient of determination ($R^2$) could be defined into various ways. Based on four kinds of $R^2$'s: two kinds are most preferred, and the other two are proposed by Liao & McGee (2003), four kinds of SSR's are derived so that the suppression for logistic models is explained. Many data fitted to logistic models are generated by Monte Carlo method. We explore when suppression happens, and compare with that for linear regression models.

Type I projection sum of squares by weighted least squares (가중최소제곱법에 의한 제1종 사영제곱합)

  • Choi, Jaesung
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.2
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    • pp.423-429
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    • 2014
  • This paper discusses a method for getting Type I sums of squares by projections under a two-way fixed-effects model when variances of errors are not equal. The method of weighted least squares is used to estimate the parameters of the assumed model. The model is fitted to the data in a sequential manner by using the model comparison technique. The vector space generated by the model matrix can be composed of orthogonal vector subspaces spanned by submatrices consisting of column vectors related to the parameters. It is discussed how to get the Type I sums of squares by using the projections into the orthogonal vector subspaces.

A Nonlinear Observer Design for Estimating State-of-Charge of Lithium Polymer Battery (리튬폴리머 배터리 잔존충전용량 추정을 위한 비선형 관측기 설계)

  • Yoo, Seog-Hwan
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.3
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    • pp.300-304
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    • 2012
  • This paper presents a nonlinear observer design method for SOC(state-of-charge) estimation of Lithium polymer battery cell. The dynamic equation of the battery cell is modeled as a simple RC electrical circuit with a nonlinear voltage source and the parameters are obtained via nonlinear optimization. Using the sum of squares decomposition, the observer gain is designed such that the error dynamics is asymptotically stable and the decay rate is below the prescribed value. In order to illustrate the performance of the observer, a computer simulation is performed using the experimental data with the UDDS(urban dynamometer driving schedule) current profile.

Estimation of Growth Curve for Evaluation of Growth Characteristics for Hanwoo cows (한우암소의 성장특성 평가를 위한 성장곡선의 추정)

  • Lee, C.W.;Choi, J.G.;Jeon, K.J.;Na, K.J.;Lee, C.;Yang, B.K.;Kim, J.B.
    • Journal of Animal Science and Technology
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    • v.45 no.4
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    • pp.509-516
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    • 2003
  • Growth curves were estimated for 1083 female Korean cattle raised in Daekwanryeong branch, National Livestock Research Institute (NLRI). Comparisons were made among various growth curve models for goodness of fit for the growth of the cows. Estimated growth curve functions were $W_t=370.2e^{-2.208e^{-0.00327t}$ for Gompertz model, for von Bertalanffy model, and $W_t=341.2(1+5.652e^{-0.00524t})^{-1}$ for Logistic model. Ages at inflection estimated from Gompertz model, von Bertalanffy model and Logistic model were 242.2 days, 191.5 days, and 330.5 days respectively, body weight at inflection were 136kg, 115kg, and 170kg, and daily gain at inflection were 0.445kg, 0.451kg, and 0.446kg. The predicted weights by ages from Gompertz model, von Bertalanffy model, and Logistic model were onsistently overestimated at birth weight and underestimated at 36 month weight. The von Bertalanffy model which had a variable point of inflection fit the data best.

Prediction for spatial time series models with several weight matrices (여러 가지 가중행렬을 가진 공간 시계열 모형들의 예측)

  • Lee, Sung Duck;Ju, Su In;Lee, So Hyun
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.1
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    • pp.11-20
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    • 2017
  • In this paper, we introduced linear spatial time series (space-time autoregressive and moving average model) and nonlinear spatial time series (space-time bilinear model). Also we estimated the parameters by Kalman Filter method and made comparative studies of power of forecast in the final model. We proposed several weight matrices such as equal proportion allocation, reciprocal proportion between distances, and proportion of population sizes. For applications, we collected Mumps data at Korea Center for Disease Control and Prevention from January 2001 until August 2008. We compared three approaches of weight matrices using the Mumps data. Finally, we also decided the most effective model based on sum of square forecast error.

Instability in nonlinear regression model (비선형회귀모형에서의 불안정성)

  • Bark, Pyeng-Mu;Kim, Youngil;Jang, Dae-Heung
    • The Korean Journal of Applied Statistics
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    • v.30 no.1
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    • pp.195-202
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    • 2017
  • We can sometimes find instability against numerical solutions in nonlinear regression. All iterative procedures in nonlinear regression require initial parameter values to be selected. Poor starting values may result in convergence to an unwanted stationary point of the error sum of squares surface. Starting values can sometimes cause the chaos effect in the nonlinear regression model. We can find the chaos phenomena with the convergence plot of starting values in the parameter space.

Variance Components of Nested Designs (지분계획의 분산성분)

  • Choi, Jaesung
    • The Korean Journal of Applied Statistics
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    • v.28 no.6
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    • pp.1093-1101
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    • 2015
  • This paper discusses nested design models when nesting occurs in treatment structure and design structure. Some are fixed and others are random; subsequently, the fixed factors having a nested design structure are assumed to be nested in the random factors. The treatment structure can involve random and fixed effects as well as a design structure that can involve several sizes of experimental units. This shows how to use projections for sums of squares by fitting the model in a stepwise procedure. Expectations of sums of squares are obtained via synthesis. Variance components of the nested design model are estimated by the method of moments.

Comparison of Reliability Estimation Methods for Ammunition Systems with Quantal-response Data (가부반응 데이터 특성을 가지는 탄약 체계의 신뢰도 추정방법 비교)

  • Ryu, Jang-Hee;Back, Seung-Jun;Son, Young-Kap
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.6
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    • pp.982-989
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    • 2010
  • This paper shows accuracy comparison results of reliability estimation methods for one-shot systems such as ammunitions. Quantal-response data, following a binomial distribution at each sampling time, characterizes lifetimes of one-shot systems. Various quantal-response data of different sample sizes are simulated using lifetime data randomly sampled from assumed weibull distributions with different shape parameters but the identical scale parameter in this paper. Then, reliability estimation methods in open literature are applied to the simulated quantal-response data to estimate true reliability over time. Rankings in estimation accuracy for different sample sizes are determined using t-test of SSE. Furthermore, MSE at each time, including both bias and variance of estimated reliability metrics for each method are analyzed to investigate how much both bias and variance contribute the SSE. From the MSE analysis, MSE provides reliability estimation trend for each method. Parametric estimation method provides more accurate reliability estimation results than the other methods for most of sample sizes.

Intra Prediction Method by Quadric Surface Modeling for Depth Video (깊이 영상의 이차 곡면 모델링을 통한 화면 내 예측 방법)

  • Lee, Dong-seok;Kwon, Soon-kak
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.2
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    • pp.35-44
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    • 2022
  • In this paper, we propose an intra-picture prediction method by a quadratic surface modeling method for depth video coding. The pixels of depth video are transformed to 3D coordinates using distance information. A quadratic surface with the smallest error is found by least square method for reference pixels. The reference pixel can be either the upper pixels or the left pixels. In the intra prediction using the quadratic surface, two predcition values are computed for one pixel. Two errors are computed as the square sums of differences between each prediction values and the pixel values of the reference pixels. The pixel sof the block are predicted by the reference pixels and prediction method that they have the lowest error. Comparing with the-state-of-art video coding method, simulation results show that the distortion and the bit rate are improved by up to 5.16% and 5.12%, respectively.