• Title/Summary/Keyword: Variance estimation

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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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    • v.14 no.1
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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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Improved Maximum Access Delay Time, Noise Variance, and Power Delay Profile Estimations for OFDM Systems

  • Wang, Hanho;Lim, Sungmook;Ko, Kyunbyoung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.12
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    • pp.4099-4113
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    • 2022
  • In this paper, we propose improved maximum access delay time, noise variance, and power delay profile (PDP) estimation schemes for orthogonal frequency division multiplexing (OFDM) system in multipath fading channels. To this end, we adopt the approximate maximum likelihood (ML) estimation strategy. For the first step, the log-likelihood function (LLF) of the received OFDM symbols is derived by utilizing only the cyclic redundancy induced by cyclic prefix (CP) without additional information. Then, the set of the initial path powers is sub-optimally obtained to maximize the derived LLF. In the second step, we can select a subset of the initial path power set, i.e. the maximum access delay time, so as to maximize the modified LLF. Through numerical simulations, the benefit of the proposed method is verified by comparison with the existing methods in terms of normalized mean square error, erroneous detection, and good detection probabilities.

Performance estimation of the noise reduction by window function on a single tone (단일 신호에 대한 창 함수의 잡음 제거 성능 평가)

  • Baek, Moon-Yeol;Kim, Byoung-Sam
    • Journal of the Korean Society for Precision Engineering
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    • v.13 no.5
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    • pp.38-43
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    • 1996
  • Windowing routines have as their purpose the reduction of the sidelobes of a spectral output of the FFT or DFT routines. Windowing routines accomplish this by forcing the beginning and end of any sequence to approach each other in value. Since they must work with any sequence they force the beginning and ending samples near zero. To make up for this reduction in power, windowing routines give extra weight to the values near the middle of the sequence. The difference between windows is the way in which they transition from the low weights near the edges to the higher weights neqr the middle of the sequence. Signal-to-noise ratio(SNR) can be determined by the ratio of the output noisy signal variance to the input noisy signal variance of a window. Standard deviation of noise is reduced by windowing. Thus, the windowing operation improved the SNR of the noisy signal. This paper shows a performance estimation of windowing on a single tone with added Gaussian noise and uniform noise.

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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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Maximum-Likelihood Estimation using a Variance-Covariance Relationship of Stochastic elements within a panel (패널내 추계적 요인들의 공분산 관계에 의한 최우추정)

  • 이회경;이진우
    • Korean Management Science Review
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    • v.11 no.2
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    • pp.29-41
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    • 1994
  • This paper analyses the stochastic nature of the Permanent Income Hypothesis (PIH) by specifying the variance-covariance structure of PIH based on Hall and Mishkin[3]. Maximum likelihood is employed to estimate the model by explicitely incorporating the heteroscedastic nature of the data into the likelihood. The data used are individual Korean household consumption and income data. The results indicate that the data are generally consistent with the Permanent Income Hypothesis, and about 11 percent of the total variation in consumption may be attributable to the excess sensitivity of consumption to income.

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Imputation using response probabilities

  • Kim, Jae-Kwang;Park, Hyeon-Ah;Jeon, Jong-Woo
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.10a
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    • pp.207-212
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    • 2003
  • In this paper, we propose a class of imputed estimators using response probability. The proposed estimator can be justified under the response probability model and thus is robust against the failure of the assumed imputation model. We also propose a variance estimator that is justified under the response probability model.

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Taylor's Power Law and Quasilikelihood

  • Park, Heung-Sun;Cho, Ki-Jong
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.10a
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    • pp.253-256
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    • 2003
  • In ecological studies, animal science, or entomology, the variance of count is considered to have the power of the mean relationship with the mean count as Taylor (1961) presented his famous 'Taylor's Power Law'. In this talk, we are going to review the development of TPL and its extension toward pest management sampling scheme. Different estimation methods are compared. Quasilikelihood approach is suggested to incorporate covariate information. Possible extensions will be discussed.

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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.

REGRESSION FRACTIONAL HOT DECK IMPUTATION

  • Kim, Jae-Kwang
    • Journal of the Korean Statistical Society
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    • v.36 no.3
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    • pp.423-434
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    • 2007
  • Imputation using a regression model is a method to preserve the correlation among variables and to provide imputed point estimators. We discuss the implementation of regression imputation using fractional imputation. By a suitable choice of fractional weights, the fractional regression imputation can take the form of hot deck fractional imputation, thus no artificial values are constructed after the imputation. A variance estimator, which extends the method of Kim and Fuller (2004), is also proposed. Results from a limited simulation study are presented.

Appropriate Choice of Window Function for Noise Reduction (잡음 감소를 위한 창 함수의 선택에 관한 연구)

  • 백문열
    • Journal of the Korean Society of Safety
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    • v.12 no.4
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    • pp.3-8
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    • 1997
  • This paper shows a performance estimation of windowing a single tone with added Gaussian noise and uniform noise. Signal-to-noise ratio can be determined by the ratio of the output noisy signal variance to the input noisy signal variance of a window. Standard deviation of noise is reduced by windowing Signal-to-noise ratio of the noisy signal is reduced by the windowing operation. Thus, performance of window function can be determined by this filtering operation that improved the signal-to-noise ratio.

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