• 제목/요약/키워드: Parameter estimator

검색결과 473건 처리시간 0.031초

The Approximate MLE in a Skew-Symmetric Laplace Distribution

  • Son, Hee-Ju;Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
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    • 제18권2호
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    • pp.573-584
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    • 2007
  • We define a skew-symmetric Laplace distribution by a symmetric Laplace distribution and evaluate its coefficient of skewness. And we derive an approximate maximum likelihood estimator(AME) and a moment estimator(MME) of a skewed parameter in a skew-symmetric Laplace distribution, and hence compare simulated mean squared errors of those estimators. We compare asymptotic mean squared errors of two defined estimators of reliability in two independent skew-symmetric distributions.

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Three level constant stress accelerated life tests for Weibull distribution

  • Moon, Gyoung Ae
    • Journal of the Korean Data and Information Science Society
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    • 제26권1호
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    • pp.281-288
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    • 2015
  • In this paper, the maximum likelihood estimators and confidence intervals for parameters of Weibull distribution are derived under three level constant stress accelerated life tests and the assumption that a log quadratic relationship exits between stress and the scale parameter ${\theta}$. The compound linear plan proposed by Kim (2006) is used to allocate the test units at each stress level, which performed nearly as good as the optimum quadratic plan and had the advantage of simplicity. Some simulation studies are given.

Simultaneous Estimation of Poisson Means

  • Lee, Seung-Ho
    • 한국수학교육학회지시리즈A:수학교육
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    • 제23권1호
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    • pp.45-50
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    • 1984
  • A problem of estimating the means of Poisson populations using independent samples is considered. The total loss is the sum of component, normalized squared error losses. An empirical Bayes estimator is derived and compared, by Monte Carlo methods, with existing estimators which are proposed as improving estimators upon the usual one. Monte Carlo results show that the performance of the derived estimator is satisfactory over the whole parameter space.

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Approximate MLE for Rayleigh Distribution in Singly Right Censored Samples

  • Jungsoo Woo;Suk-Bok Kang;Young-Suk Cho;Sangchoon Jeon
    • Communications for Statistical Applications and Methods
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    • 제5권1호
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    • pp.225-230
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    • 1998
  • By assuming a singly right cenosred sample, we propose the approximate maximum likelihood estimator (AMLE) of the scale parameter of the p-dimensional Rayleigh distribution. We compare the proposed estimator in ·terms of the mean squared error through Monte Carlo methods.

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Estimation in an Exponentiated Half Logistic Distribution under Progressively Type-II Censoring

  • Kang, Suk-Bok;Seo, Jung-In
    • Communications for Statistical Applications and Methods
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    • 제18권5호
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    • pp.657-666
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    • 2011
  • In this paper, we derive the maximum likelihood estimator(MLE) and some approximate maximum likelihood estimators(AMLEs) of the scale parameter in an exponentiated half logistic distribution based on progressively Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error(MSE) through a Monte Carlo simulation for various censoring schemes. We also obtain the AMLEs of the reliability function.

부하관측기와 신경망에 의해 설정된 파라미터의 DSP 적용에 의한 3상 유도전동기의 실시간 제어 (The Real-Time Control of 3-Phase Induction Motor by DSP Application of Tuning Parameter Using Load Torque Observer and Neural Network)

  • 권양원;윤양웅;강학수;안태천
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.135-135
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    • 2000
  • In this Paper. the DSP implementation of induction motor drive is Presented on the viewpoint of the design and experiment. The speed estimation of control system for induction motor drive is designed on the base of neural network speed estimator. This neural network speed estimator is experimentally applied to the induction motor system. This system Provides the satisfactory results.

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Parameter Estimation for an Infinite Dimensional Stochastic Differential Equation

  • Kim, Yoon-Tae
    • Journal of the Korean Statistical Society
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    • 제25권2호
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    • pp.161-173
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    • 1996
  • When we deal with a Hilbert space-valued Stochastic Differential Equation (SDE) (or Stochastic Partial Differential Equation (SPDE)), depending on some unknown parameters, the solution usually has a Fourier series expansion. In this situation we consider the maximum likelihood method for the statistical estimation problem and derive the asymptotic properties (consistency and normality) of the Maximum Likelihood Estimator (MLE).

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A Method of Choosing a Value of the Bending Constant in Huber's M-Estimation Function

  • Park, Ro-Jin
    • Journal of the Korean Data and Information Science Society
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    • 제11권2호
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    • pp.181-188
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    • 2000
  • The shape of an M-estimation function is generally determined in the sense of either/both maximizing efficiency of an M-estimator at the model or/and bounding the influence function of an M-estimator. We propose an empirical method of choosing a value of the bending constant in Huber's ${\psi}-function$, which is the most widely used M-estimation function when estimating the location parameter.

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Improved Exponential Estimator for Estimating the Population Mean in the Presence of Non-Response

  • Kumar, Sunil
    • Communications for Statistical Applications and Methods
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    • 제20권5호
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    • pp.357-366
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    • 2013
  • This paper defines an improvement for estimating the population mean of a study variable using auxiliary information and known values of certain population parameter(s), when there is a non-response in a study as well as on auxiliary variables. Under a simple random sampling without a replacement (SRSWOR) scheme, the mean square error (MSE) of all proposed estimators are obtained and compared with each other. Numerical illustration is also given.

Parameter Estimation for a Hilbert Space-valued Stochastic Differential Equation ?$\pm$

  • Kim, Yoon-Tae;Park, Hyun-Suk
    • Journal of the Korean Statistical Society
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    • 제31권3호
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    • pp.329-342
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    • 2002
  • We deal with asymptotic properties of Maximum Likelihood Estimator(MLE) for the parameters appearing in a Hilbert space-valued Stochastic Differential Equation(SDE) and a Stochastic Partial Differential Equation(SPDE). In paractice, the available data are only the finite dimensional projections to the solution of the equation. Using these data we obtain MLE and consider the asymptotic properties as the dimension of projections increases. In particular we explore a relationship between the conditions for the solution and asymptotic properties of MLE.