• Title/Summary/Keyword: Minimum Variance

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Estimation of Smoothing Constant of Minimum Variance and its Application to Industrial Data

  • Takeyasu, Kazuhiro;Nagao, Kazuko
    • Industrial Engineering and Management Systems
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    • v.7 no.1
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    • pp.44-50
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    • 2008
  • Focusing on the exponential smoothing method equivalent to (1, 1) order ARMA model equation, a new method of estimating smoothing constant using exponential smoothing method is proposed. This study goes beyond the usual method of arbitrarily selecting a smoothing constant. First, an estimation of the ARMA model parameter was made and then, the smoothing constants. The empirical example shows that the theoretical solution satisfies minimum variance of forecasting error. The new method was also applied to the stock market price of electrical machinery industry (6 major companies in Japan) and forecasting was accomplished. Comparing the results of the two methods, the new method appears to be better than the ARIMA model. The result of the new method is apparently good in 4 company data and is nearly the same in 2 company data. The example provided shows that the new method is much simpler to handle than ARIMA model. Therefore, the proposed method would be better in these general cases. The effectiveness of this method should be examined in various cases.

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.

The Realization of State-Space Digital Filters with Minimum Output Error Variance by Weighted Function (가중함수에 의한 최소 출력오차 분산을 갖는 상태공간 디지틀 필터 실현)

  • 김정화;정찬수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.17 no.9
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    • pp.909-917
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    • 1992
  • This paper proposes the realization of state-space digital filters with minimum output error variance. The algorithm is transforms of controllability and observability gramian in linear time invariant systems by weighted function and can improve performance of the digital filters by reducing the put error variance for state space coeffient variation. A numerical example shows that algorithm structure has much lower output error variance than that of other four structures(canonical, parallel, statistical sensitivity, balanced).

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Hedge Effectiveness in Won-Dollar Futures Markets (원 달러 선물시장을 이용한 헤지효과성)

  • Hong, Chung-Hyo;Moon, Gyu-Hyun
    • The Korean Journal of Financial Management
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    • v.21 no.1
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    • pp.231-253
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    • 2004
  • We examine hedge strategies that use Won-dollar futures to hedge the price risk of the Won-dollar exchange rate. We employ the naive hedge model, minimum variance hedge model and bivariate ECT-ARCH(1) model as hedge instruments, and analyze their hedge performances. The sample period covers from January 2, 2001 to December 31, 2002 with sub-samples such as daily, weekly, bi-weekly prices of the Won-dollar futures and cash. The important findings may be summarized as follows. First, there is no significant difference in hedge ratio between the risk minimum variance model and bivariate ECT-ARCH(1) model that controls for the cointegration relationship of the Won-dollar futures and cash. Second, hedge performance of the naive model and minimum variance model with constant hedge ratios is not far behind that of bivariate ECT-ARCH(1) model with time-varying hedge ratios. This results imply that investors are encouraged to use the minimum variance hedge model to hedge Won-dollar exchange rate with Won-dollar futures. Third, hedge performance and effectiveness of each model is also analyzed with respect to hedge period appear to be greater over long than over the short period. This evidence supports the hypothesis that futures prices would have more time to respond to the greater cash price changes over the longer holding period, leading to an improved hedge performance.

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A self tuning controller using genetic algorithms (유전 알고리듬을 이용한 자기동조 제어기)

  • 조원철;김병문;이평기
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.629-632
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    • 1997
  • This paper presents the design method of controller which is combined Genetic Algorithms with the Generalized minimum variance self tuning controller. It is shown that the controllers adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a polynomial parameters. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.

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Blind Multi-User Detector Using Code-Constrained Minimum Variance Method (코드 제한 최소 분산 방법을 이용한 블라인드 다중 사용자 검파기)

  • 임상훈;정형성이충용윤대희
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.215-218
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    • 1998
  • This paper proposes a blind multi-user detector using Code-Constrained Minimum Variance (CCMV) method which directly detects the DS-CDMA signals in a multipath fading channel without estimating the channels. This algorithm reduces the complexity of computation by making a small size data matrix with the order of the channel length. Advantageously it requires to know the spreading code and the time delay of only the desired user.

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The Three-Stage Cluster Unrelated Question Model

  • Ahn, Seung-Chul;Lee, Gi-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.1
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    • pp.55-65
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    • 2003
  • In this study, we systemize the theoretical validity for applying unrelated question model to three-stage cluster sampling method and derive the estimate and it's variance of sensitive parameter. We derive the minimum variance form under the optimal values of the subsample sizes when the cost are fixed. Under the some given precision, we obtain the optimal values of the subsample sizes and derive the minimum cost form by using them.

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Estimation for a bivariate survival model based on exponential distributions with a location parameter

  • Hong, Yeon Woong
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.4
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    • pp.921-929
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    • 2014
  • A bivariate exponential distribution with a location parameter is proposed as a model for a two-component shared load system with a guarantee time. Some statistical properties of the proposed model are investigated. The maximum likelihood estimators and uniformly minimum variance unbiased estimators of the parameters, mean time to failure, and the reliability function of system are obtained with unknown guarantee time. Simulation studies are given to illustrate the results.

ESTIMATION OF HURST PARAMETER AND MINIMUM VARIANCE SPECTRUM

  • Kim, Joo-Mok
    • Korean Journal of Mathematics
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    • v.26 no.2
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    • pp.155-166
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    • 2018
  • Consider FARIMA time series with innovations that have infinite variances. We are interested in the estimation of self-similarities $H_n$ of FARIMA(0, d, 0) by using modified R/S statistic. We can confirm that the $H_n$ converges to Hurst parameter $H=d+\frac{1}{2}$. Finally, we figure out ARMA and minimum variance power spectrum density of FARIMA processes.