• 제목/요약/키워드: minimum variance estimator

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Length-biased Rayleigh distribution: reliability analysis, estimation of the parameter, and applications

  • Kayid, M.;Alshingiti, Arwa M.;Aldossary, H.
    • International Journal of Reliability and Applications
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    • 제14권1호
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    • pp.27-39
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    • 2013
  • In this article, a new model based on the Rayleigh distribution is introduced. This model is useful and practical in physics, reliability, and life testing. The statistical and reliability properties of this model are presented, including moments, the hazard rate, the reversed hazard rate, and mean residual life functions, among others. In addition, it is shown that the distributions of the new model are ordered regarding the strongest likelihood ratio ordering. Four estimating methods, namely, method of moment, maximum likelihood method, Bayes estimation, and uniformly minimum variance unbiased, are used to estimate the parameters of this model. Simulation is used to calculate the estimates and to study their properties. Finally, the appropriateness of this model for real data sets is shown by using the chi-square goodness of fit test and the Kolmogorov-Smirnov statistic.

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역가우스분포에 대한 변형된 엔트로피 기반 적합도 검정 (A Modi ed Entropy-Based Goodness-of-Fit Tes for Inverse Gaussian Distribution)

  • 최병진
    • 응용통계연구
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    • 제24권2호
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    • pp.383-391
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    • 2011
  • 이 논문에서는 역가우스분포의 적합을 위한 변형된 엔트로피 기반 검정을 제시한다. 이 검정은 자료생성분포와 역가우스분포의 엔트로피 차이에 기초를 두고 있으며 검정통계량은 엔트로피 차이의 추정량을 사용한다. 엔트로피 차이의 추정량은 자료생성분포에 대한 엔트로피 추정량으로 Vasicek의 표본엔트로피와 역가우스분포에 대한 엔트로피 추정량로 균일최소분산불편추정량을 사용하여 얻는다. 모의실험을 통해 얻은 표본크기와 윈도크기에 따른 검정통계량의 기각값들을 표의 형태로 제공한다. 제안한 검정의 검정력 알아보기 위해 여러 대립분포와 표본크기에 대해서 모의실험을 수행하고 기존의 엔트로피 기반 검정과 비교한다.

이산형 칼만 필터를 이용한 서보 시스템의 추정자 설계 (Design of an Estimator for Servo Systems using Discrete Kalman Filter)

  • 신두진;허욱열
    • 대한전기학회논문지:전력기술부문A
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    • 제48권8호
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    • pp.996-1003
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    • 1999
  • This paper propose a position-speed controller with an estimator which can estimate states and disturbance. The overall control system consists of two parts: the position-speed controller and an estimator. The Kalman filter applied as state-feedback controller is an optimal state estimator applied to a dynamic system that involves random perturbations and gives a linear, unbiased and minimum error variance recursive algorithm to optimally estimate the unknown state. Therefore, we consider the error problem about the servo system modeling and the measurement noise as a stochastic system and implement a optimal state observer, and enhance the estimate performance of position and speed using that. Using two-degree-of freedom(TDOF) conception, we design the command input response and the closed loop characteristics independently. The servo system is to improve the closed loop characteristics without affecting the command imput response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer using a inverse-transfer matrix. Therefore, the performance of overall position-speed controller is enhanced. Finally, the performance of the proposed controller is exemplified by some simulations and by applying the real servo system.

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A Study on Individual Tap-Power Estimation for Improvement of Adaptive Equalizer Performance

  • Kim, Nam-Yong
    • Journal of electromagnetic engineering and science
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    • 제4권1호
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    • pp.23-29
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    • 2004
  • In this paper we analyze convergence constraints and time constant of IT-LMS algorithm and derive a method of making it's time constant independent of signal power by using input variance estimation. The method for estimating the input variance is to use a single-pole low-pass filter(LPF) with common smoothing parameter value, θ. The estimator is with narrow bandwidth for large θ but with wide bandwidth for small θ. This small θ gives long term average estimation(low frequency) of the fluctuating input variance well as short term variations (high frequency) of the input power. In our simulations of multipath communication channel equalization environments, the method with large θ has shown not as much improved convergence speed as the speed of the original IT-LMS algorithm. The proposed method with small θ=0.01 reach its minimum MSE in 100 samples whereas the IT-LMS converges in 200 samples. This shows the proposed, tap-power normalized IT-LMS algorithm can be applied more effectively to digital wireless communication systems.

Admissible Hierarchical Bayes Estimators of a Multivariate Normal Mean Shrinking towards a Regression Surface

  • Cho, Byung-Yup;Choi, Kuey-Chung;Chang, In-Hong
    • Communications for Statistical Applications and Methods
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    • 제3권2호
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    • pp.205-216
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    • 1996
  • Consider the problem of estimating a multivariate normal mean with an unknown covarience matrix under a weighted sum of squared error losses. We first provide hierarchical Bayes estimators which shrink the usual (maximum liklihood, uniformly minimum variance unbiased) estimator towards a regression surface and then prove the admissibility of these estimators using Blyth's (1951) method.

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A Projected Exponential Family for Modeling Semicircular Data

  • Kim, Hyoung-Moon
    • 응용통계연구
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    • 제23권6호
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    • pp.1125-1145
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    • 2010
  • For modeling(skewed) semicircular data, we derive a new exponential family of distributions. We extend it to the l-axial exponential family of distributions by a projection for modeling any arc of arbitrary length. It is straightforward to generate samples from the l-axial exponential family of distributions. Asymptotic result reveals that the linear exponential family of distributions can be used to approximate the l-axial exponential family of distributions. Some trigonometric moments are also derived in closed forms. The maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for a goodness of t test of the l-axial exponential family of distributions. Samples of orientations are used to demonstrate the proposed model.

ESTIMATING VARIOUS MEASURES IN NORMAL POPULATION THROUGH A SINGLE CLASS OF ESTIMATORS

  • Sharad Saxena;Housila P. Singh
    • Journal of the Korean Statistical Society
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    • 제33권3호
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    • pp.323-337
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    • 2004
  • This article coined a general class of estimators for various measures in normal population when some' a priori' or guessed value of standard deviation a is available in addition to sample information. The class of estimators is primarily defined for a function of standard deviation. An unbiased estimator and the minimum mean squared error estimator are worked out and the suggested class of estimators is compared with these classical estimators. Numerical computations in terms of percent relative efficiency and absolute relative bias established the merits of the proposed class of estimators especially for small samples. Simulation study confirms the excellence of the proposed class of estimators. The beauty of this article lies in estimation of various measures like standard deviation, variance, Fisher information, precision of sample mean, process capability index $C_{p}$, fourth moment about mean, mean deviation about mean etc. as particular cases of the proposed class of estimators.

종속 지수 성분을 가지는 병렬시스템의 신뢰도 추정 (Estimation of Reliability for a Parallel System with Dependent Exponential Components)

  • 안정향;윤상철
    • 한국산업정보학회논문지
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    • 제8권4호
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    • pp.94-100
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    • 2003
  • 본 논문에서는k개 성분들이 지수분포를 따르는 병렬시스템에서 하나의 성분이 고장났을 때 나머지성분들의 수명분포에 영향을 줄 때 주어진 시각 t 에서 시스템의 신뢰도, 위험함수, 평균잔여수명, 신뢰도에 대한 최우추정량과 최소분산불편추정량을 제시하고 그리고 모의실험을 통하여 추정량들의 효율성을 연구한다.

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BLUE-Based Channel Estimation Technique for Amplify and Forward Wireless Relay Networks

  • PremKumar, M.;SenthilKumaran, V.N.;Thiruvengadam, S.J.
    • ETRI Journal
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    • 제34권4호
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    • pp.511-517
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    • 2012
  • The best linear unbiased estimator (BLUE) is most suitable for practical application and can be determined with knowledge of only the first and second moments of the probability density function. Although the BLUE is an existing algorithm, it is still largely unexplored and has not yet been applied to channel estimation in amplify and forward (AF)-based wireless relay networks (WRNs). In this paper, a BLUE-based algorithm is proposed to estimate the overall channel impulse response between the source and destination of AF strategy-based WRNs. Theoretical mean square error (MSE) performance for the BLUE is derived to show the accuracy of the proposed channel estimation algorithm. In addition, the Cram$\acute{e}$r-Rao lower bound (CRLB) is derived to validate the MSE performance. The proposed BLUE channel estimation algorithm approaches the CRLB as the length of the training sequence and number of relays increases. Further, the BLUE performs better than the linear minimum MSE estimator due to the minimum variance characteristic exhibited by the BLUE, which happens to be a function of signal-to-noise ratio.

파레토분포(分布)에서 두 모수(母數)의 함수(函數) 추정(推定) (Estimation for Functions of Two Parameters in the Pareto Distribution)

  • 우정수;강석복
    • Journal of the Korean Data and Information Science Society
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    • 제1권
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    • pp.67-76
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    • 1990
  • For a two-parameter Pareto distribution, the uniformly minimum variance unbiased estimateors(UMVUE) for the function of the two parameters are expressed in terms of confluent hypergeometric function. The variance of the UMVUE is also expressed in terms of hypergeometric function of several variables. UMVUE's for the ${\gamma}th$ moment about zero and several useful parametric functions, and their variances are obtained as special cases. The estimators of Baxter(1980) and Saksena and Johnson(1984) are special cases of our estimator.

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