• 제목/요약/키워드: maximum likelihood estimation

검색결과 984건 처리시간 0.024초

A Robust Estimation for the Composite Lognormal-Pareto Model

  • Pak, Ro Jin
    • Communications for Statistical Applications and Methods
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    • 제20권4호
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    • pp.311-319
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    • 2013
  • Cooray and Ananda (2005) proposed a composite lognormal-Pareto model to analyze loss payment data in the actuarial and insurance industries. Their model is based on a lognormal density up to an unknown threshold value and a two-parameter Pareto density. In this paper, we implement the minimum density power divergence estimation for the composite lognormal-Pareto density. We compare the performances of the minimum density power divergence estimator (MDPDE) and the maximum likelihood estimator (MLE) by simulations and an example. The minimum density power divergence estimator performs reasonably well against various violations in the distribution. The minimum density power divergence estimator better fits small observations and better resists against extraordinary large observations than the maximum likelihood estimator.

단발 터어보프롭 항공기 동적 모델의 파라메터추정 (Parameter estimation of a single turbo-prop aircraft dynamic model)

  • 이환;이상기
    • 제어로봇시스템학회논문지
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    • 제4권1호
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    • pp.38-44
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    • 1998
  • The modified maximum likelihood estimation method is used to estimate the nondimensional aerodynamic derivatives of a single turbo-prop aircraft at a specified flight condition for the best deduction of the dynamic characteristics. In wind axes the six degree of freedom equations are algebraically linearized so that the linear state equation contains aerodynamic derivatives in a state-space form and is used in the maximum likelihood method. The simulated data added with the measurement noise is used as a flight test data which is necessary to the estimation of nondimensional aerodynamic derivatives. It is obtained by implementing the 6-DOF nonlinear flight simulation. In the flight simulation, the effects of several control input types, control deflection amplitudes, and the turbulence intensities on the statistical convergence criteria are also examined and quantitative analysis of the results is discussed.

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New generalized inverse Weibull distribution for lifetime modeling

  • Khan, Muhammad Shuaib;King, Robert
    • Communications for Statistical Applications and Methods
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    • 제23권2호
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    • pp.147-161
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    • 2016
  • This paper introduces the four parameter new generalized inverse Weibull distribution and investigates the potential usefulness of this model with application to reliability data from engineering studies. The new extended model has upside-down hazard rate function and provides an alternative to existing lifetime distributions. Various structural properties of the new distribution are derived that include explicit expressions for the moments, moment generating function, quantile function and the moments of order statistics. The estimation of model parameters are performed by the method of maximum likelihood and evaluate the performance of maximum likelihood estimation using simulation.

Constrained Estimation of the Numbers of Trials in Several Binomial Populations

  • Oh, Myongsik;Lee, Eun-Kyoung
    • Communications for Statistical Applications and Methods
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    • 제7권3호
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    • pp.699-709
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    • 2000
  • The constrained maximum likelihood estimation of the number of trials in several binomial populations under order restriction, such as simple order, is discussed. The estimation procedure is based on, so called, pool adjacent violators algorithm. Three handy estimators are given and their performances are compared using an artificial example.

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Estimation of the exponentiated half-logistic distribution based on multiply Type-I hybrid censoring

  • Jeon, Young Eun;Kang, Suk-Bok
    • Communications for Statistical Applications and Methods
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    • 제27권1호
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    • pp.47-64
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    • 2020
  • In this paper, we derive some estimators of the scale parameter of the exponentiated half-logistic distribution based on the multiply Type-I hybrid censoring scheme. We assume that the shape parameter λ is known. We obtain the maximum likelihood estimator of the scale parameter σ. The scale parameter is estimated by approximating the given likelihood function using two different Taylor series expansions since the likelihood equation is not explicitly solved. We also obtain Bayes estimators using prior distribution. To obtain the Bayes estimators, we use the squared error loss function and general entropy loss function (shape parameter q = -0.5, 1.0). We also derive interval estimation such as the asymptotic confidence interval, the credible interval, and the highest posterior density interval. Finally, we compare the proposed estimators in the sense of the mean squared error through Monte Carlo simulation. The average length of 95% intervals and the corresponding coverage probability are also obtained.

Estimation for Exponential Distribution Under Multiple Type-II Censoring

  • 강석복;류세기
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2003년도 추계학술대회
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    • pp.13-18
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    • 2003
  • When the available sample is multiply type-II censored, the maximum likelihood estimators of the location and scale parameters of two- parameter exponential distribution do not exist explicitly. In this case, we propose several approximate maximum likelihood estimators by approximating the likelihood equations appropriately. We present an example to illustrate these estimation methods.

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A Cholesky Decomposition of the Inverse of Covariance Matrix

  • Park, Jong-Tae;Kang, Chul
    • Journal of the Korean Data and Information Science Society
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    • 제14권4호
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    • pp.1007-1012
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    • 2003
  • A recursive procedure for finding the Cholesky root of the inverse of sample covariance matrix, leading to a direct solution for the inverse of a positive definite matrix, is developed using the likelihood equation for the maximum likelihood estimation of the Cholesky root under normality assumptions. An example of the Hilbert matrix is considered for an illustration of the procedure.

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ORDER RESTRICTED STATISTICAL INFERENCE ON LORENZ CURVES OF PARETO DISTRIBUTIONS

  • Oh, Myongsik
    • Journal of applied mathematics & informatics
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    • 제13권1_2호
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    • pp.457-470
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    • 2003
  • The comparison of two or more Lorenz curves of Pareto distributions of first kind under arbitrary order restriction is studied. The problem is turned out to be a statistical inference problem concerning scale parameters under order restriction. We assume that the location parameters of Palate distributions are completely unknown. In this paper the maximum likelihood estimation and likelihood ratio tests for and against order restriction are proposed.

On Estimating the Parameters of an Extended Form of Logarithmic Series Distribution

  • Kumar, C. Satheesh;Riyaza, A.
    • Communications for Statistical Applications and Methods
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    • 제20권5호
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    • pp.417-425
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    • 2013
  • We consider an extended version of a logarithmic series distribution and discuss the estimation of its parameters by the method of moments and the method of maximum likelihood. Test procedures are suggested to test the significance of the additional parameter of this distribution and all procedures are illustrated with the help of real life data sets. In addition, a simulation study is conducted to assess the performance of the estimators.

스트레스 한계가 있는 램프시험하에서 신뢰수명분포의 최우추정: 사용조건에서부터 스트레스를 가하는 경우 (Maximum Likelihood Estimation of Lifetime Distribution under Stress Bounded Ramp Tests: The Case Where Stress Loaded from Use Condition)

  • 전영록
    • 품질경영학회지
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    • 제25권2호
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    • pp.1-14
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    • 1997
  • This paper considers maximum likelihood (ML) estimation of lifetime distribution under stress bounded ramp tests in which the stress is increased linearly from used condition stress to the stress u, pp.r bound. The following assumptions are used: exponential lifetime distribution under a constant stress, an inverse power law relationship between stress and mean of exponential lifetime distribution, and a cumulative exposure model for the effect of changing stress. Likelihood equations for the parameters involved in the model and asymptotic distribution of the estimators are obtained, and a numerical example is given.

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