• Title/Summary/Keyword: Maximum likelihood model

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Exponentiated Quasi Lindley distribution

  • Elbatal, I.;Diab, L.S.;Elgarhy, M.
    • International Journal of Reliability and Applications
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    • v.17 no.1
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    • pp.1-19
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    • 2016
  • The Exponentiated Quasi Lindley (EQL) distribution which is an extension of the quasi Lindley Distribution is introduced and its properties are explored. This new distribution represents a more flexible model for the lifetime data. Some statistical properties of the proposed distribution including the shapes of the density and hazard rate functions, the moments and moment generating function, the distribution of the order statistics are given. The maximum likelihood estimation technique is used to estimate the model parameters and finally an application of the model with a real data set is presented for the illustration of the usefulness of the proposed distribution.

Reliability for Series and Parallel Systems in Bivariate Pareto Model : Random Censorship Case

  • Cho, Jang-Sik;Cho, Kil-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.3
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    • pp.461-469
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    • 2003
  • In this paper, we consider the series and parallel system which include two components. We assume that the lifetimes of two components follow the bivariate Pareto model with random censored data. We obtain the estimators and approximated confidence intervals of the reliabilities for series and parallel systems based on maximum likelihood estimator and the relative frequency, respectively. Also we present a numerical example by giving a data set which is generated by computer.

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The Least Absolute Deviations Estimation of the Contingent Valuation Model (조건부가치측정모형의 최소절대편차추정)

  • Kim, Dongil
    • Environmental and Resource Economics Review
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    • v.10 no.4
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    • pp.515-545
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    • 2001
  • This paper introduces the least absolute deviations estimation of the contingent valuation model, which corresponds to the semi-parametric estimation of discrete choice models by Manski (1975, 1985) and Lee (1992). The least absolute deviations estimation is more robust to mis-specified distributional assumptions in the estimation of the contingent valuation model, compared to the maximum likelihood estimation. The full identification and strong consistency of the estimation are proved and its application to different formats of contingent valuation survey data is discussed. Simulation studies are designed to evaluate its operational characteristics including computational strategies, small sample properties and the efficiency gain of a follow-up question. The bias and efficiency of least absolute deviations and maximum likelihood estimation are compared in the presence of heteroskedasticity.

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Software Reliability Model with Multiple Change-Points (소프트웨어 신뢰도 모형에서 다중 변화점 문제)

  • Dong Hoon Lim;Dong Hee Kim
    • The Korean Journal of Applied Statistics
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    • v.7 no.2
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    • pp.101-111
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    • 1994
  • In this paper, we can see that software reliability model has been improved by considering multiple change-points. The condition for the existence of maximum likelihood estimate of the initial error content of a program is given and the maximum likelihood estimations of multiple change-points are derived. We assess the performance of our multiple change-points model on numerical applicaiton.

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Semi-Continuous Hidden Markov Model with the MIN Module (MIN 모듈을 갖는 준연속 Hidden Markov Model)

  • Kim, Dae-Keuk;Lee, Jeong-Ju;Jeong, Ho-Kyoun;Lee, Sang-Hee
    • Speech Sciences
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    • v.7 no.4
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    • pp.11-26
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    • 2000
  • In this paper, we propose the HMM with the MIN module. Because initial and re-estimated variance vectors are important elements for performance in HMM recognition systems, we propose a method which compensates for the mismatched statistical feature of training and test data. The MIN module function is a differentiable function similar to the sigmoid function. Unlike a continuous density function, it does not include variance vectors of the data set. The proposed hybrid HMM/MIN module is a unified network in which the observation probability in the HMM is replaced by the MIN module neural network. The parameters in the unified network are re-estimated by the gradient descent method for the Maximum Likelihood (ML) criterion. In estimating parameters, the variance vector is not estimated because there is no variance element in the MIN module function. The experiment was performed to compare the performance of the proposed HMM and the conventional HMM. The experiment measured an isolated number for speaker independent recognition.

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Parameters Estimation of Generalized Linear Failure Rate Semi-Markov Reliability Models

  • El-Gohary, A.;Al-Khedhair, A.
    • International Journal of Reliability and Applications
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    • v.11 no.1
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    • pp.1-16
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    • 2010
  • In this paper we will discuss the stochastic analysis of a three state semi-Markov reliability model. Maximum likelihood procedure will be used to obtain the estimators of the parameters included in this reliability model. Based on the assumption that the lifetime and repair time of the system units are generalized linear failure rate random variables, the reliability function of this system is obtained. Also, the distribution of the first passage time of this system will be derived. Some important special cases are discussed.

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Comparison of different estimators of P(Y

  • Hassan, Marwa KH.
    • International Journal of Reliability and Applications
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    • v.18 no.2
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    • pp.83-98
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    • 2017
  • Stress-strength reliability problems arise frequently in applied statistics and related fields. In the context of reliability, the stress-strength model describes the life of a component, which has a random strength X and is subjected to random stress Y. The component fails at the instant that the stress applied to it exceeds the strength and the component will function satisfactorily whenever X > Y. The problem of estimation the reliability parameter in a stress-strength model R = P[Y < X], when X and Y are two independent two-parameter Lindley random variables is considered in this paper. The maximum likelihood estimator (MLE) and Bayes estimator of R are obtained. Also, different confidence intervals of R are obtained. Simulation study is performed to compare the different proposed estimation methods. Example in real data is used as practical application of the proposed procedure.

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Optimal three step stress accelerated life tests under periodic inspection and type I censoring

  • Moon, Gyoung-Ae
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.4
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    • pp.843-850
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    • 2012
  • The inferences of data obtained from periodic inspection and type I censoring for the three step stress accelerated life test are studied in this paper. The failure rate function that a log-quadratic relation of stress and the tampered failure rate model are considered under the exponential distribution. The optimal stress change times which minimize the asymptotic variance of maximum likelihood estimators of parameters is determined and the maximum likelihood estimators of the model parameters are estimated. A numerical example will be given to illustrate the proposed inferential procedures.

Reliability estimation for shared load model with guarantee time under censoring scheme (중도절단계획 하에서 보증시간을 가지는 부하분배모형의 신뢰도추정)

  • Cha, Young-Joon
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.3
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    • pp.467-474
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    • 2009
  • There are many situations arising in reliability engineering and biomedical science where failure of a subsystem increases the failure rate of other subsystem under shared load models. In this paper, the maximum likelihood estimates and the modified maximum likelihood estimates of mean time to failure and reliability function for shared load model with guarantee time are obtained by using censored system life data. Some illustrative examples are included.

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Note on the Consistency of a Penalized Maximum Likelihood Estimate (벌점가능추정치의 일치성에 대하여)

  • Ahn, Sung-Mahn
    • Communications for Statistical Applications and Methods
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    • v.16 no.4
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    • pp.573-578
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    • 2009
  • We prove the consistency of a penalized maximum likelihood estimate proposed by Ahn (2001). The PMLE not only avoids the well-known problem that the ordinary likelihood of the normal mixture model is unbounded for any given sample size, but also removes redundant components.