• 제목/요약/키워드: the least-squares method

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Multiclass Classification via Least Squares Support Vector Machine Regression

  • Shim, Joo-Yong;Bae, Jong-Sig;Hwang, Chang-Ha
    • Communications for Statistical Applications and Methods
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    • 제15권3호
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    • pp.441-450
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    • 2008
  • In this paper we propose a new method for solving multiclass problem with least squares support vector machine(LS-SVM) regression. This method implements one-against-all scheme which is as accurate as any other approach. We also propose cross validation(CV) method to select effectively the optimal values of hyper-parameters which affect the performance of the proposed multiclass method. Experimental results are then presented which indicate the performance of the proposed multiclass method.

Weighted Least Absolute Error Estimation of Regression Parameters

  • Song, Moon-Sup
    • Journal of the Korean Statistical Society
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    • 제8권1호
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    • pp.23-36
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    • 1979
  • In the multiple linear regression model a class of weighted least absolute error estimaters, which minimize the sum of weighted absolute residuals, is proposed. It is shown that the weighted least absolute error estimators with Wilcoxon scores are equivalent to the Koul's Wilcoxon type estimator. Therefore, the asymptotic efficiency of the proposed estimator with Wilcoxon scores relative to the least squares estimator is the same as the Pitman efficiency of the Wilcoxon test relative to the Student's t-test. To find the estimates the iterative weighted least squares method suggested by Schlossmacher is applicable.

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Simultaneous Kinetic Spectrophotometric Determination of Sulfite and Sulfide Using Partial Least Squares (PLS) Regression

  • Afkhami, Abbas;Sarlak, Nahid;Zarei, Ali Reza;Madrakian, Tayyebeh
    • Bulletin of the Korean Chemical Society
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    • 제27권6호
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    • pp.863-868
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    • 2006
  • The partial least squares (PLS-1) calibration model based on spectrophotometric measurement, for the simultaneous determination of sulfite and sulfide is described. This method is based on the difference between the rate of the reaction of sulfide and sulfite with Malachite Green in pH 7.0 buffer solution and at 25 ${^{\circ}C}$. The absorption kinetic profiles of the solutions were monitored by measuring the decrease in the absorbance of Malachite Green at 617 nm in the time range 10-180 s after initiation of the reactions with 2 s intervals. The experimental calibration matrix for partial least squares (PLS-1) calibration was designed with 24 samples. The cross-validation method was used for selecting the number of factors. The results showed that simultaneous determination could be performed in the range 0.030-1.5 and 0.030-1.2 $\mu$g m$L ^{-1}$ for sulfite and sulfide, respectively. The proposed method was successfully applied to simultaneous determination of sulfite and sulfide in water samples and whole human blood.

Conservative Quadratic RSM combined with Incomplete Small Composite Design and Conservative Least Squares Fitting

  • Kim, Min-Soo;Heo, Seung-Jin
    • Journal of Mechanical Science and Technology
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    • 제17권5호
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    • pp.698-707
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    • 2003
  • A new quadratic response surface modeling method is presented. In this method, the incomplete small composite design (ISCD) is newly proposed to .educe the number of experimental runs than that of the SCD. Unlike the SCD, the proposed ISCD always gives a unique design assessed on the number of factors, although it may induce the rank-deficiency in the normal equation. Thus, the singular value decomposition (SVD) is employed to solve the normal equation. Then, the duality theory is used to newly develop the conservative least squares fitting (CONFIT) method. This can directly control the ever- or the under-estimation behavior of the approximate functions. Finally, the performance of CONFIT is numerically shown by comparing its'conservativeness with that of conventional fitting method. Also, optimizing one practical design problem numerically shows the effectiveness of the sequential approximate optimization (SAO) combined with the proposed ISCD and CONFIT.

Application of GPS Surveying for Extracting Highway's Horizontal Alignment

  • Seo, Jeong-Hoon;Roh, Tae-Ho;Lee, Jong-Chool
    • Korean Journal of Geomatics
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    • 제2권1호
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    • pp.1-6
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    • 2002
  • Korea is a small country with relatively large mountainous areas and has many difficulties from planning to completing one road. Maintaining a completed road presents even more difficulties. presently, in estimating design elements, the result varies according to the engineer and there are many cases that question the reliability of the results. Therefore, in this study, the alignment of highway was sampled using by the centerline path, the design elements of horizontal alignment were reduced by applying the Least Squares Method, and the accuracy was analyzed. By this method, IP, IA, R, $\Delta$R and A-parameter were also determined. By observing relatively long straight sections, the approximate values could be estimated, and particularly, the considerably accurate value of A-parameter was determined. This study, using the Least Squares Method, aims to contribute to the development of the alignment examination in frequent traffic accident regions.

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Modified partial least squares method implementing mixed-effect model

  • Kyunga Kim;Shin-Jae Lee;Soo-Heang Eo;HyungJun Cho;Jae Won Lee
    • Communications for Statistical Applications and Methods
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    • 제30권1호
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    • pp.65-73
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    • 2023
  • Contemporary biomedical data often involve an ill-posed problem owing to small sample size and large number of multi-collinear variables. Partial least squares (PLS) method could be a plausible alternative to an ill-conditioned ordinary least squares. However, in the case of a PLS model that includes a random-effect, how to deal with a random-effect or mixed effects remains a widely open question worth further investigation. In the present study, we propose a modified multivariate PLS method implementing mixed-effect model (PLSM). The advantage of PLSM is its versatility in handling serial longitudinal data or its ability for taking a randomeffect into account. We conduct simulations to investigate statistical properties of PLSM, and showcase its real clinical application to predict treatment outcome of esthetic surgical procedures of human faces. The proposed PLSM seemed to be particularly beneficial 1) when random-effect is conspicuous; 2) the number of predictors is relatively large compared to the sample size; 3) the multicollinearity is weak or moderate; and/or 4) the random error is considerable.

Estimation of viscous and Coulomb damping from free-vibration data by a least-squares curve-fitting analysis

  • Slemp, Wesley C.H.;Hallauer, William L. Jr.;Kapania, Rakesh K.
    • Smart Structures and Systems
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    • 제4권3호
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    • pp.279-290
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    • 2008
  • The modeling and parameter estimation of a damped one-degree-of-freedom mass-spring system is examined. This paper presents a method for estimating the system parameters (damping coefficients and natural frequency) from measured free-vibration motion of a system that is modeled to include both subcritical viscous damping and kinetic Coulomb friction. The method applies a commercially available least-squares curve-fitting software function to fit the known solution of the equations of motion to the measured response. The method was tested through numerical simulation, and it was applied to experimental data collected from a laboratory mass-spring apparatus. The mass of this apparatus translates on linear bearings, which are the primary source of light inherent damping. Results indicate that the curve-fitting method is effective and accurate for both perfect and noisy measurements from a lightly damped mass-spring system.

WorldView-2 pan-sharpening by minimization of spectral distortion with least squares

  • Choi, Myung-Jin
    • 대한원격탐사학회지
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    • 제27권3호
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    • pp.353-357
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    • 2011
  • Although the intensity-hue-saturation (IHS) method for pan-sharpening has a spectral distortion problem, it is a popular method in the remote sensing community and has been used as a standard procedure in many commercial packages due to its fast computing and easy implementation. Recently, IHS-like approaches have tried to overcome the spectral distortion problem inherited from the IHS method itself and yielded a good result. In this paper, a similar IHS-like method with least squares for WorldView-2 pan-sharpening is presented. In particular, unlike the previous methods with three or four-band multispectral images for pan-sharpening, six bands of WorldView-2 multispectral image located within the range of panchromatic spectral radiance responses are considered in order to reduce the spectral distortion during the merging process. As a result, the new approach provides a satisfactory result, both visually and quantitatively. Furthermore, this shows great value in spectral fidelity of WorldView-2 eight-band multispectral imagery.

Mixture Filtering Approaches to Blind Equalization Based on Estimation of Time-Varying and Multi-Path Channels

  • Lim, Jaechan
    • Journal of Communications and Networks
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    • 제18권1호
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    • pp.8-18
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    • 2016
  • In this paper, we propose a number of blind equalization approaches for time-varying andmulti-path channels. The approaches employ cost reference particle filter (CRPF) as the symbol estimator, and additionally employ either least mean squares algorithm, recursive least squares algorithm, or $H{\infty}$ filter (HF) as a channel estimator such that they are jointly employed for the strategy of "Rao-Blackwellization," or equally called "mixture filtering." The novel feature of the proposed approaches is that the blind equalization is performed based on direct channel estimation with unknown noise statistics of the received signals and channel state system while the channel is not directly estimated in the conventional method, and the noise information if known in similar Kalman mixture filtering approach. Simulation results show that the proposed approaches estimate the transmitted symbols and time-varying channel very effectively, and outperform the previously proposed approach which requires the noise information in its application.

ANALYSIS OF FIRST-ORDER SYSTEM LEAST-SQUARES FOR THE OPTIMAL CONTROL PROBLEMS FOR THE NAVIER-STOKES EQUATIONS

  • Choi, Young-Mi;Kim, Sang-Dong;Lee, Hyung-Chun;Shin, Byeong-Chun
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제11권4호
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    • pp.55-68
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    • 2007
  • First-order least-squares method of a distributed optimal control problem for the incompressible Navier-Stokes equations is considered. An optimality system for the optimal solution are reformulated to the equivalent first-order system by introducing velocity-flux variables and then the least-squares functional corresponding to the system is defined in terms of the sum of the squared $L^2$ norm of the residual equations of the system. The optimal error estimates for least-squares finite element approximations are obtained.

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