• Title/Summary/Keyword: Unbiased estimator

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A BLUE Estimator for Passive Localization by TDOA Method (TDOA 방식 기반 위치 추정을 위한 BLUE 추정기)

  • Lee, Young-Kyu;Yang, Sung-Hoon;Kwon, Taeg-Yong;Lee, Chang-Bok;Park, Byung-Koo;Lee, Won-Jin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.11C
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    • pp.702-711
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    • 2011
  • In this paper, we derived a closed-form equation of a Best Linear Unbiased Estimator (BLUE) and its Crammer-Rao Lower Bound (CRLB) for the estimation of the position of the emitter based on the Time Difference of Arrival (TDOA) teclmique. The BLUE and CRLB were derived for the case of estimating 2 dimensional position of the emitter with 3 base stations or sensors, and for this purpose, we nsed an approximated equation of the TDOA hyperbola equation obtained from the first order Taylor-series after setting the reference points of the position. The derived equation can be used for any kind of noises which are uncorrelated in each other in the TOA measurement noises and for a white Gaussian noise also.

Condition assessment of bridge pier using constrained minimum variance unbiased estimator

  • Tamuly, Pranjal;Chakraborty, Arunasis;Das, Sandip
    • Structural Monitoring and Maintenance
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    • v.7 no.4
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    • pp.319-344
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    • 2020
  • Inverse analysis of non-linear reinforced concrete bridge pier using recursive Gaussian filtering for in-situ condition assessment is the main theme of this work. For this purpose, minimum variance unbiased estimation using unscented sigma points is adopted here. The uniqueness of this inverse analysis lies in its approach for strain based updating of engineering demand parameters, where appropriate bound and constrained conditions are introduced to ensure numerical stability and convergence. In this analysis, seismic input is also identified, which is an added advantage for the structures having no dedicated sensors for earthquake measurement. First, the proposed strategy is tested with a simulated example whose hysteretic properties are obtained from the slow-cyclic test of a frame to investigate its efficiency and accuracy. Finally, the experimental test data of a full-scale bridge pier is used to study its in-situ condition in terms of Park & Ang damage index. Overall the study shows the ability of the augmented minimum variance unbiased estimation based recursive time-marching algorithm for non-linear system identification with the aim to estimate the engineering damage parameters that are the fundamental information necessary for any future decision making for retrofitting/rehabilitation.

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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    • v.34 no.4
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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.

Robust Total Least Squares Method and its Applications to System Identifications (견인한 완전최소자승법과 시스템 식별에의 적용)

  • Kim, Jin-Young;Choi, Seung-Ho
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.4
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    • pp.93-97
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    • 1996
  • The Total Least Squares(TLS) method is an unbiased estimator for solving overdetermined sets of linear equations Ax${\simeq}$b when errors occur in all data. However, as well as Least Squares(LS) method it doesn't show robustness while the errors have a heavy tailed probability density function. In this paper we proposed a robust method of TLS (Robust TLS, ROTLS) based on the characteristics of TLS solution. And the ROTLS is verified by applying it to system identification problems.

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A bias adjusted ratio-type estimator (편향 보정 비형태추정량에 관한 연구)

  • Oh, Jung-Taek;Shin, Key-Il
    • The Korean Journal of Applied Statistics
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    • v.31 no.3
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    • pp.397-408
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    • 2018
  • Various methods for accurate parameter estimation have been developed in a sample survey and it is also common to use a ratio estimator or the regression estimator using auxiliary information. The ratio-type estimator has been used in many recent studies and is known to improve the accuracy of estimation by adjusting the ratio estimator. However, various studies are under way to solve it since the ratio-type estimator is biased. In this study, we propose a generalized ratio-type estimator with a new parameter added to the ratio-type estimator to remove the bias. We suggested a method to apply this result to the parameter estimation under the error assumption of heteroscedasticity. Through simulation, we confirmed that the suggested generalized ratio-type estimator gives good results compared to conventional ratio-type estimators.

Estimation of the Population Mean in Presence of Non-Response

  • Kumar, Sunil;Bhougal, Sandeep
    • Communications for Statistical Applications and Methods
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    • v.18 no.4
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    • pp.537-548
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    • 2011
  • In this paper following Singh et al. (2008), we propose a modified ratio-product type exponential estimator to estimate the finite population mean $\={Y}$ of the study variable y in presence of non-response in different situations viz. (i) population mean $\={X}$ is known, and (ii) population mean $\={X}$ is unknown. The expressions of biases and mean squared error of the proposed estimators have been obtained under large sample approximation using single as well as double sampling. Some realistic conditions have been obtained under which the proposed estimator is more efficient than usual unbiased estimators, ratio estimators, product estimators and exponential ratio and product estimators reported by Rao (1986) and Singh et al. (2010) are found to be more efficient in many situations.

Bayes Estimation of Reliability in the Strength-Stress Models

  • Yum, Joon-Keun;Kim, Jae-Joo;Cho, Sin-Sup;Park, Hong-Nai
    • Journal of Korean Society for Quality Management
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    • v.22 no.2
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    • pp.69-78
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    • 1994
  • We obtain the Bayes estimator(BE), the minimum variance unbiased estimator(MVUE) and maximun likelihood estimator(MLE) of the reliability when the distribution of the stress and the strength are Weibull with known shape parameters. The experiment is terminated before all of the items on the test have failed and the failed items are partially replaced. Performance of the three estimators for moderate size samples are compared through Monte Carlo simulation.

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Approximate Confidence Limits for the Ratio of Two Binomial Variates with Unequal Sample Sizes

  • Cho, Hokwon
    • Communications for Statistical Applications and Methods
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    • v.20 no.5
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    • pp.347-356
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    • 2013
  • We propose a sequential method to construct approximate confidence limits for the ratio of two independent sequences of binomial variates with unequal sample sizes. Due to the nonexistence of an unbiased estimator for the ratio, we develop the procedure based on a modified maximum likelihood estimator (MLE). We generalize the results of Cho and Govindarajulu (2008) by defining the sample-ratio when sample sizes are not equal. In addition, we investigate the large-sample properties of the proposed estimator and its finite sample behavior through numerical studies, and we make comparisons from the sample information view points.

On the Cramer-Rao Bound for Estimating Parameters of Exponentially Decaying Function under Poisson Noise (Poisson 잡음 하에서의 지수 감소 함수 인자 추정시의 Cramer-Rao bound)

  • Seok, Ji-Yeong;Kim, Jeong-Tae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.1
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    • pp.101-104
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    • 2013
  • We computed Cramer-Rao bound for estimating amplitude and decay parameters of exponentially decaying function under Poisson noise. Since Cramer-Rao bound is the lowest variance bound for any unbiased estimator, the computed Cramer-Rao bound can be used for evaluating the performance of estimators under Poisson noise. In addition, we show that the performance of maximum-likelihood estimator is close to the Cramer-Rao bound by simulations.