• 제목/요약/키워드: function parameter

검색결과 2,967건 처리시간 0.031초

Diagnostics for Estimated Smoothing Parameter by Generalized Maximum Likelihood Function (일반화최대우도함수에 의해 추정된 평활모수에 대한 진단)

  • Jung, Won-Tae;Lee, In-Suk;Jeong, Hae-Jeong
    • Journal of the Korean Data and Information Science Society
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    • 제7권2호
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    • pp.257-262
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    • 1996
  • When we are estimate the smoothing parameter in spline regression model, we deal the diagnostic of influence observations as posteriori analysis. When we use Generalized Maximum Likelihood Function as the estimation method of smoothing parameter, we propose the diagnostic measure for influencial observations in the obtained estimate, and we introduce the finding method of the proper smoothing parameter estimate.

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Measurement of Spatial coherence function and Directional coherence function of Propagating Laser Beam by using Wigner Distribution Function

  • Lee, Chang-Hyuck;Kang, Yoon-Shik;Noh, Jae-Woo
    • Proceedings of the Optical Society of Korea Conference
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    • 한국광학회 2009년도 동계학술발표회 논문집
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    • pp.449-450
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    • 2009
  • The spatial coherence and propagation property of laser beam propagating through several optical components were studied experimentally by using the measurement of Wigner distribution function. It is shown experimentally that the Wigner function measurement yields total degree of coherence, beam quality parameter, and the near and the far field information of the propagating beam. More complete characterization of the laser beam was achieved by applying the Schmidt mode decomposition to the Wigner distribution function, spatial coherence function and directional coherence function. Fine details of coherence property are understood by the characteristics of the contributing eigenmodes.

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Effect of Window Function for Measurement of Ultrasonic Nonlinear Parameter Using Fast Fourier Transform of Tone-Burst Signal (톤버스트 신호의 퓨리에 변환을 이용한 초음파 비선형 파라미터 측정에서 창함수가 미치는 영향)

  • Lee, Kyoung-Jun;Kim, Jongbeom;Song, Dong-Gi;Jhang, Kyung-Young
    • Journal of the Korean Society for Nondestructive Testing
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    • 제35권4호
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    • pp.251-257
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    • 2015
  • In ultrasonic nonlinear parameter measurement using the fast Fourier transform(FFT) of tone-burst signals, the side lobe and leakage on spectrum because of finite time and non-periodicity of signals makes it difficult to measure the harmonic magnitudes accurately. The window function made it possible to resolve this problem. In this study, the effect of the Hanning and Turkey window functions on the experimental measurement of nonlinear parameters was analyzed. In addition, the effect of changes in tone burst signal number with changes in the window function on the experimental measurement was analyzed. The result for both window functions were similar and showed that they enabled reliable nonlinear parameter measurement. However, in order to restore original signal amplitude, the amplitude compensation coefficient should be considered for each window function. On a separate note, the larger number of tone bursts was advantageous for stable nonlinear parameter measurement, but this effect was more advantageous in the case of the Hanning window than the Tukey window.

Calibration and Estimation of Parameter for Storage Function Model (저류함수모형의 매개변수 보정 및 추정)

  • Kim, Bum Jun;Kawk, Jae Won;Lee, Jin Hee;Kim, Hung Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • 제28권1B호
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    • pp.21-32
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    • 2008
  • Flood forecasting is a very important tool as one of nonstructural measures for reduction of flood damages in life and property and its accuracy is also an important factor. However, when we apply the Storage Function Model(SFM) which is mainly used for the flood forecasting system in Korea, the determination of the parameters is very important but it is difficult. So, the parameters have been calibrated by using an empirical formulas and judgement of hydrologist. Hence, in this study we perform the sensitivity analysis to understand the parameter characteristics and establish the ranges of parameters of the SFM. Also we do the parameter calibration by using the optimization techniques and objective functions, and evaluate their performances. Especially, we suggest a method to determine proper parameters by using a objective function which can be obtained from flood events. So, we use the suggested method for parameter estimation and compare the estimated parameters with the previously reported parameters. As a result of the application, the estimated parameters by the suggested method showed better than them from the previously reported parameters.

An Edge-Based Algorithm for Discontinuity Adaptive Image Smoothing (에지기반의 불연속 경계적응 영상 평활화 알고리즘)

  • 강동중;권인소
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.273-273
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    • 2000
  • We present a new scheme to increase the performance of edge-preserving image smoothing from the parameter tuning of a Markov random field (MRF) function. The method is based on automatic control of the image smoothing-strength in MRF model ing in which an introduced parameter function is based on control of enforcing power of a discontinuity-adaptive Markov function and edge magnitude resulted from discontinuities of image intensity. Without any binary decision for the edge magnitude, adaptive control of the enforcing power with the full edge magnitude could improve the performance of discontinuity-preserving image smoothing.

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Noninformative priors for the reliability function of two-parameter exponential distribution

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • 제22권2호
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    • pp.361-369
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    • 2011
  • In this paper, we develop the reference and the matching priors for the reliability function of two-parameter exponential distribution. We derive the reference priors and the matching prior, and prove the propriety of joint posterior distribution under the general prior including the reference priors and the matching prior. Through the sim-ulation study, we show that the proposed reference priors match the target coverage probabilities in a frequentist sense.

Estimation for the Power Function Distribution Based on Type- II Censored Samples

  • Kang, Suk-Bok;Jung, Won-Tae
    • Journal of the Korean Data and Information Science Society
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    • 제19권4호
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    • pp.1335-1344
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    • 2008
  • The maximum likelihood method does not admit explicit solutions when the sample is multiply censored and progressive censored. So we shall propose some approximate maximum likelihood estimators (AMLEs) of the scale parameter for the power function distribution based on multiply Type-II censored samples and progressive Type-II censored samples when shape parameter is known. We compare the proposed estimators in the sense of the mean squared error (MSE) through Monte Carlo simulation for various censoring schemes.

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Kernel Machine for Poisson Regression

  • Hwang, Chang-Ha
    • Journal of the Korean Data and Information Science Society
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    • 제18권3호
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    • pp.767-772
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    • 2007
  • A kernel machine is proposed as an estimating procedure for the linear and nonlinear Poisson regression, which is based on the penalized negative log-likelihood. The proposed kernel machine provides the estimate of the mean function of the response variable, where the canonical parameter is related to the input vector in a nonlinear form. The generalized cross validation(GCV) function of MSE-type is introduced to determine hyperparameters which affect the performance of the machine. Experimental results are then presented which indicate the performance of the proposed machine.

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A Combination Capture-Recapture and Line Transect Model in Clustered Population

  • Choi, Jin-Sik;Pyong, Nam-Kung
    • Communications for Statistical Applications and Methods
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    • 제6권3호
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    • pp.729-748
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    • 1999
  • In this paper we present combined estimator of capture-recapture and line transect model using bivariate detection function and detection probability according to objects being in cluster population. Here bivariate detection function use distance and cluster size. The simulation shows that combined estimator approaches the more true value the larger size parameter. Therefore this estimator using the bivariate detection function is more efficient in estimate the population size and density by size parameter.

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ESTIMATION OF SCALE PARAMETER AND P(Y < X) FROM RAYLEIGH DISTRIBUTION

  • Kim, Chan-Soo;Chung, Youn-Shik
    • Journal of the Korean Statistical Society
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    • 제32권3호
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    • pp.289-298
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    • 2003
  • We consider the estimation problem for the scale parameter of the Rayleigh distribution using weighted balanced loss function (WBLF) which reflects both goodness of fit and precision. Under WBLF, we obtain the optimal estimator which creates a kind of balance between Bayesian and non-Bayesian estimation. We also deal with the estimation of R = P(Y < X) when Y and X are two independent but not identically distributed Rayleigh distribution under squared error loss function.