• Title/Summary/Keyword: maximum likelihood estimation

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Identification of Linear Structural Systems (선형 구조계의 동특성 추정법)

  • 윤정방
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1989.10a
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    • pp.46-50
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    • 1989
  • Methods for the estimation of the coefficient matrices in the equation of motion for a linear multi-degree-of-freedom structure arc studied. For this purpose, the equation of motion is transformed into an auto-regressive and moving average with auxiliary input (ARMAX) model. The ARMAX parameters are evaluated using several methods of parameter estimation; such as toe least squares, the instrumental variable, the maximum likelihood and the limited Information maximum likelihood methods. Then the parameters of the equation of motion are recovered therefrom. Numerical example is given for a 3-story building model subjected to an earthquake exitation.

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On the Estimation of Parameters in ALT under Generalized Exponential Distribution

  • Yoon, Sang-Chul
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.923-931
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    • 2005
  • The two parameter generalized exponential distribution was recently introduced by Gupta and Kundu (1999). It is observed that the generalized exponential distribution can be used quite effectively to analyze skewed data set. This paper develops the accelerated life test model using generalized exponential distribution and considers maximum likelihood estimation of parameters under the tampered random variable model. To show the performance of proposed maximum likelihood estimates, some simulation will be performed. Using a real data set, an example will be given.

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Estimation for the scale parameter of Weibull Distribution Based on Multiply Censored Samples

  • Han, Jun-Tae;Kang, Suk-Bok;Lee, Hwa-Jung
    • 한국데이터정보과학회:학술대회논문집
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    • 2004.04a
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    • pp.83-90
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    • 2004
  • We consider the problem of estimating the scale parameter of the Weibull distribution based on multiply Type-II censord samples. We propose some estimators by using the approximate maximum likelihood estimation method. The proposed estimators are compared in the sense of the mean squared error.

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DIRECTIONAL LOG-DENSITY ESTIMATION

  • Huh, Jib;Kim, Peter T.;Koo, Ja-Yong;Park, Jin-Ho
    • Journal of the Korean Statistical Society
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    • v.33 no.3
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    • pp.255-269
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    • 2004
  • This paper develops log-density estimation for directional data. The methodology is to use expansions with respect to spherical harmonics followed by estimating the unknown parameters by maximum likelihood. Minimax rates of convergence in terms of the Kullback-Leibler information divergence are obtained.

A Study on Estimation of Parameters in Bivariate Exponential Distribution

  • Kim, Jae Joo;Park, Byung-Gu
    • Journal of Korean Society for Quality Management
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    • v.15 no.1
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    • pp.20-32
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    • 1987
  • Estimation for the parameters of a bivariate exponential (BVE) model of Marshall and Olkin (1967) is investigated for the cases of complete sampling and time-truncated parallel sampling. Maximum likelihood estimators, method of moment estimators and Bayes estimators for the parameters of a BVE model are obtained and compared with each other. A Monte Cario simulation study for a moderate sized samples indicates that the Bayes estimators of parameters perform better than their maximum likelihood and method of moment estimators.

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Estimation for Two-Parameter Generalized Exponential Distribution Based on Records

  • Kang, Suk Bok;Seo, Jung In;Kim, Yongku
    • Communications for Statistical Applications and Methods
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    • v.20 no.1
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    • pp.29-39
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    • 2013
  • This paper derives maximum likelihood estimators (MLEs) and some approximate MLEs (AMLEs) of unknown parameters of the generalized exponential distribution when data are lower record values. We derive approximate Bayes estimators through importance sampling and obtain corresponding Bayes predictive intervals for unknown parameters for lower record values from the generalized exponential distribution. For illustrative purposes, we examine the validity of the proposed estimation method by using real and simulated data.

Hybrid Speaker Adaptation using Maximum-Likelihood Estimation (MLE를 이용한 하이브리드 화자 적응)

  • 표현아;김세현;오영환
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.268-270
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    • 2002
  • 최근 음성 인식 시스템의 성능 향상을 위해 화자 적응 (speaker adaptation)에 대한 연구가 활발히 진행되고 있다. HMM 기반 인식 시스템의 모델 파라미터를 수정하는 화자 적응의 경우, MAP방법과 MLLR 방법에 대한 연구가 주류를 이루고 있다. 두 방법은 adaptation data의 양에 따라서 서로 다른 성능을 보인다. 본 논문에서는 기존 두 방법을 Maximum-likelihood Estimation(MLE)를 이용하여 화자 적응을 수행하는 방법을 제안한다. 제안한 방법을 KAIST 통신연구실에서 구축한 한국어 도시이름 500단어 인식 시스템에 적용하여 adaptation data의 양에 상관없이 항상 높은 성능을 나타냈으며, 기존의 방법에 대해서 최고 4.37%의 인식률 향상을 보였다.

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Estimation of Weibull Scale Parameter Based on Multiply Type-II Censored Samples

  • Kang, Suk-Bok;Lee, Hwa-Jung;Han, Jun-Tae
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.3
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    • pp.593-603
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    • 2004
  • We consider the problem of estimating the scale parameter of the Weibull distribution based on multiply Type-II censored samples. We propose two estimators by using the approximate maximum likelihood estimation method for Weibull and extreme value distributions. The proposed estimators are compared in the sense of the mean squared error.

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Bayes Estimation of Two Ordered Exponential Means

  • Hong, Yeon-Woong;Kwon, Yong-Mann
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.1
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    • pp.273-284
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    • 2004
  • Bayes estimation of parameters is considered for two independent exponential distributions with ordered means. Order restricted Bayes estimators for means are obtained with respect to inverted gamma, noninformative prior and uniform prior distributions, and their asymptotic properties are established. It is shown that the maximum likelihood estimator, restricted maximum likelihood estimator, unrestricted Bayes estimator, and restricted Bayes estimator of the mean are all consistent and have the same limiting distribution. These estimators are compared with the corresponding unrestricted Bayes estimators by Monte Carlo simulation.

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Avoiding Indefiniteness in Criteria for Maximum Likelihood Bearing Estimation with Arbitrary Array Configuration

  • Suzuki, Masakiyo
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.1807-1810
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    • 2002
  • This paper presents a technique for avoid- ing indefiniteness in Maximum Likelihood (ML) criteria for Direction-of-Arrival (DOA) finding using a sensor ar- ray with arbitrary configuration. The ML criterion has singular points in the solution space where the criterion becomes indefinite. Solutions fly iterative techniques for ML bearing estimation may oscillate because of numerical instability which occurs due to the indefiniteness, when bearings more than one approach to the identical value. The oscillation makes the condition for terminating iterations complex. This paper proposes a technique for avoiding the indefiniteness in ML criteria.

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