• Title/Summary/Keyword: Variance estimation

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Frequency/Amplitude Separation Algorithm Using the Higher Order Differential Energy Operator and Its Application (고차의 미분에너지함수를 이용한 주파수 및 진폭성분 추출 알고리즘과 응용)

  • Iem, Byeong-Gwan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.8
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    • pp.1498-1502
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    • 2007
  • There have been many different definitions of energy functions as the second statistics of a signal. In this paper, using the higher order differential energy function, we propose an algorithm separating the amplitude and frequency components in a discrete sinusoidal signal. The proposed amplitude and frequency estimation methods have less computational requirement than the existing methods. It also shows large computational advantage over the root mean square (RMS) calculation of a signal. The proposed methods can be used in the detection of abnormal events in signals on the power line. Computer simulations show that proposed frequency estimation method can detect the presence of voltage increase or decrease for a short period of time. Also, the proposed estimation methods have been compared with existing methods in terms of estimation error variance.

Optimal Estimation within Class of James-Stein Type Decision Rules on the Known Norm

  • Baek, Hoh Yoo
    • Journal of Integrative Natural Science
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    • v.5 no.3
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    • pp.186-189
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    • 2012
  • For the mean vector of a p-variate normal distribution ($p{\geq}3$), the optimal estimation within the class of James-Stein type decision rules under the quadratic loss are given when the underlying distribution is that of a variance mixture of normals and when the norm ${\parallel}\underline{{\theta}}{\parallel}$ in known. It also demonstrated that the optimal estimation within the class of Lindley type decision rules under the same loss when the underlying distribution is the previous type and the norm ${\parallel}{\theta}-\overline{\theta}\underline{1}{\parallel}$ with $\overline{\theta}=\frac{1}{p}\sum\limits_{i=1}^{n}{\theta}_i$ and $\underline{1}=(1,{\cdots},1)^{\prime}$ is known.

Review of Parameter Estimation Procedure of Freund Bivariate Exponential Distribution (Freund 이변량 지수분포의 매개변수 추정과정 검토)

  • Park, Cheol-Soon;Yoo, Chul-Sang
    • Journal of Korea Water Resources Association
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    • v.45 no.2
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    • pp.191-201
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    • 2012
  • This study reviewed the parameter estimation procedure of the Freund bivariate exponential distribution for the decision of the annual maximum rainfall event. The method of moments was reviewed first, whose results were compared with those from the method of maximum likelihood. Both methods were applied to the hourly rainfall data of the Seoul rain gauge station measured from 1961 to 2010 to select the annual maximum rainfall events, which were also compared each other. The results derived are as follows. First, when applying the method of moments for the parameter estimation, it was found necessary to consider the correlation coefficient between the two variables as well as the mean and variance. Second, the method of maximum likelihood was better to reproduce the mean, but the method of moments was better to reproduce the annual variation of the variance. Third, The annual maximum rainfall events derived were very similar in both cases. Among differently selected annual maximum rainfall events, those with the higher rainfall amount were selected by the method of maximum likelihood, but those with the higher rainfall intensity by the method of moments.

Estimation of Additive and Dominance Genetic Variances in Line Breeding Swine

  • Ishida, T.;Kuroki, T.;Harada, H.;Fukuhara, R.
    • Asian-Australasian Journal of Animal Sciences
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    • v.14 no.1
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    • pp.1-6
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    • 2001
  • Additive and dominance genetic variances were estimated for purebred Landrace selected with line breeding from 1989 to 1995 at Miyazaki Livestock Experiment Station, Kawaminami Branch. Ten body measurements, two reproductive traits and fifteen carcass traits were analyzed with single-trait mixed model analysis. The estimates of narrow-sense heritabilities by additive model were in the range of 0.07 to 0.46 for body measurements, 0.05 to 0.14 for reproductive traits, and 0.05 to 0.68 for carcass traits. The additive model tended to slightly overestimate the narrow-sense heritabilities as compared to the additive and dominance model. The proportion of the dominance variance to total genetic variance ranged from 0.11 to 0.91 for body measurements, 0.00 to 0.65 for reproductive traits, and 0.00 to 0.86 for carcass traits. Large differences among traits were found in the ratio of dominance to total genetic variance. These results suggested that dominance effect would affect the expression of all ten body measurements, one reproductive trait, and nine carcass traits. It is justified to consider the dominance effects in genetic evaluation of the selected lines for those traits.

Comparison of Two Parametric Estimators for the Entropy of the Lognormal Distribution (로그정규분포의 엔트로피에 대한 두 모수적 추정량의 비교)

  • Choi, Byung-Jin
    • Communications for Statistical Applications and Methods
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    • v.18 no.5
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    • pp.625-636
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    • 2011
  • This paper proposes two parametric entropy estimators, the minimum variance unbiased estimator and the maximum likelihood estimator, for the lognormal distribution for a comparison of the properties of the two estimators. The variances of both estimators are derived. The influence of the bias of the maximum likelihood estimator on estimation is analytically revealed. The distributions of the proposed estimators obtained by the delta approximation method are also presented. Performance comparisons are made with the two estimators. The following observations are made from the results. The MSE efficacy of the minimum variance unbiased estimator appears consistently high and increases rapidly as the sample size and variance, n and ${\sigma}^2$, become simultaneously small. To conclude, the minimum variance unbiased estimator outperforms the maximum likelihood estimator.

Observed Data Oriented Bispectral Estimation of Stationary Non-Gaussian Random Signals - Automatic Determination of Smoothing Bandwidth of Bispectral Windows

  • Sasaki, K.;Shirakata, T.
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.502-507
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    • 2003
  • Toward the development of practical methods for observed data oriented bispectral estimation, an automatic means for determining the smoothing bandwidth of bispectral windows is proposed, that can also provide an associated optimum bispectral estimate of stationary non-Gaussian signals, systematically only from an observed time series datum of finite length. For the conventional non-parametric bispectral estimation, the MSE (mean squared error) of the normalized estimate is reviewed under a certain mixing condition and sufficient data length, mainly from the viewpoint of the inverse relation between its bias and variance with respect to the smoothing bandwidth. Based on the fundamental relation, a systematic method not only for determining the bandwidth, but also for obtaining the optimum bispectral estimate is presented by newly introducing a MSE evaluation index of the estimate only from an observed time series datum of finite length. The effectiveness and fundamental features of the proposed method are illustrated by the basic results of numerical experiments.

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Graphical Diagnostics for Logistic Regression

  • Lee, Hak-Bae
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.05a
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    • pp.213-217
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    • 2003
  • In this paper we discuss graphical and diagnostic methods for logistic regression, in which the response is the number of successes in a fixed number of trials.

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Optimal Designs for Multivariate Nonparametric Kernel Regression with Binary Data

  • Park, Dong-Ryeon
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.243-248
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    • 1995
  • The problem of optimal design for a nonparametric regression with binary data is considered. The aim of the statistical analysis is the estimation of a quantal response surface in two dimensions. Bias, variance and IMSE of kernel estimates are derived. The optimal design density with respect to asymptotic IMSE is constructed.

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Statistical Analysis of Generalized Capon's Method

  • Jinho Choi
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1994.06a
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    • pp.925-930
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    • 1994
  • We consider statistical properties of the generalized Capon's method. It is observed that the estimation error of the generalized Capon's method has almost the same variance as the MUSIC method, although the generalized Capon's method yields a slightly biased estimate.

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On the Efficient Teaching Method of Confidence Interval in College Education

  • Kim, Yeung-Hoon;Ko, Jeong-Hwan
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.4
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    • pp.1281-1288
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    • 2008
  • The purpose of this study is to consider the efficient methods for introducing the confidence interval. We explain various concepts and approaches about the confidence interval estimation. Computing methods for calculating the efficient confidence interval are suggested.

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