• Title/Summary/Keyword: Modified maximum likelihood estimator

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Approximate Maximum Likelihood Estimation for the Three-Parameter Weibull Distribution

  • Kang, S.B.;Cho, Y.S.;Choi, S.H.
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.209-217
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    • 2001
  • We obtain the approximate maximum likelihood estimators (AMLEs) for the scale and location parameters $\theta$ and $\mu$ in the three-parameter Weibull distribution based on Type-II censored samples. We also compare the AMLEs with the modified maximum likelihood estimators (MMLEs) in the sense of the mean squared error (MSE) based on complete sample.

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Modified inverse moment estimation: its principle and applications

  • Gui, Wenhao
    • Communications for Statistical Applications and Methods
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    • v.23 no.6
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    • pp.479-496
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    • 2016
  • In this survey, we present a modified inverse moment estimation of parameters and its applications. We use a specific model to demonstrate its principle and how to apply this method in practice. The estimation of unknown parameters is considered. A necessary and sufficient condition for the existence and uniqueness of maximum-likelihood estimates of the parameters is obtained for the classical maximum likelihood estimation. Inverse moment and modified inverse moment estimators are proposed and their properties are studied. Monte Carlo simulations are conducted to compare the performances of these estimators. As far as the biases and mean squared errors are concerned, modified inverse moment estimator works the best in all cases considered for estimating the unknown parameters. Its performance is followed by inverse moment estimator and maximum likelihood estimator, especially for small sample sizes.

Goodness-of-fit Test for the Weibull Distribution Based on Multiply Type-II Censored Samples

  • Kang, Suk-Bok;Han, Jun-Tae
    • Communications for Statistical Applications and Methods
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    • v.16 no.2
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    • pp.349-361
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    • 2009
  • In this paper, we derive the approximate maximum likelihood estimators of the shape parameter and the scale parameter in a Weibull distribution under multiply Type-II censoring by the approximate maximum likelihood estimation method. We develop three modified empirical distribution function type tests for the Weibull distribution based on multiply Type-II censored samples. We also propose modified normalized sample Lorenz curve plot and new test statistic.

Goodness-of-fit Test for the Extreme Value Distribution Based on Multiply Type-II Censored Samples

  • Kang, Suk-Bok;Cho, Young-Seuk;Han, Jun-Tae
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.4
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    • pp.1441-1448
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    • 2008
  • We propose the modified quantile-quantile (Q-Q) plot using the approximate maximum likelihood estimators and the modified normalized sample Lorenz curve (NSLC) plot for the extreme value distribution based on multiply Type-II censored samples. Using two example data sets, we picture the modified Q-Q plot and the modified NSLC plot.

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Higber Order Expansions of the Cumulants and the Modified Normalizing Process of Multi-dimensional Maximum Likelihood Estimator

  • Jonghwa Na
    • Communications for Statistical Applications and Methods
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    • v.6 no.1
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    • pp.305-318
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    • 1999
  • In this paper we derive the higher order expansions of the first four cumulants of multi-dimensional Maximum Likelihood Estimator (MLE) under the general parametric model up to and including terms of order O({{{{ {n }^{-1 } }}}}) Also we obtain the explicit form of the expansion of the normalizing trans formation of multi-dimensional MLE and show that the suggested normalizing process is much better than the normal approximation based on central limit theorem through example.

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A COMPARATIVE EVALUATION OF THE ESTIMATORS OF THE 2-PARAMETER GENERALIZED PARETO DISTRIBUTION

  • Singh, V.P.;Ahmad, M.;Sherif, M.M.
    • Water Engineering Research
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    • v.4 no.3
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    • pp.155-173
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    • 2003
  • Parameters and quantiles of the 2-parameter generalized Pareto distribution were estimated using the methods of regular moments, modified moments, probability weighted moments, linear moments, maximum likelihood, and entropy for Monte Carlo-generated samples. The performance of these seven estimators was statistically compared, with the objective of identifying the most robust estimator. It was found that in general the methods of probability-weighted moments and L-moments performed better than the methods of maximum likelihood estimation, moments and entropy, especially for smaller values of the coefficient of variation and probability of exceedance.

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Goodness-of-fit test for the logistic distribution based on multiply type-II censored samples

  • Kang, Suk-Bok;Han, Jun-Tae;Cho, Young-Seuk
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.1
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    • pp.195-209
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    • 2014
  • In this paper, we derive the estimators of the location parameter and the scale parameter in a logistic distribution based on multiply type-II censored samples by the approximate maximum likelihood estimation method. We use four modified empirical distribution function (EDF) types test for the logistic distribution based on multiply type-II censored samples using proposed approximate maximum likelihood estimators. We also propose the modified normalized sample Lorenz curve plot for the logistic distribution based on multiply type-II censored samples. For each test, Monte Carlo techniques are used to generate the critical values. The powers of these tests are also investigated under several alternative distributions.

Bayesian Inference for Modified Jelinski-Moranda Model by using Gibbs Sampling (깁스 샘플링을 이용한 변형된 Jelinski-Moranda 모형에 대한 베이지안 추론)

  • 최기헌;주정애
    • Journal of Applied Reliability
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    • v.1 no.2
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    • pp.183-192
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    • 2001
  • Jelinski-Moranda model and modified Jelinski-Moranda model in software reliability are studied and we consider maximum likelihood estimator and Bayes estimates of the number of faults and the fault-detection rate per fault. A gibbs sampling approach is employed to compute the Bayes estimates, future survival function is examined. Model selection based on prequential likelihood of the conditional predictive ordinates. A numerical example with simulated data set is given.

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Test for the Exponential Distribution Based on Multiply Type-II Censored Samples

  • Kang, Suk-Bok;Lee, Sang-Ki
    • Communications for Statistical Applications and Methods
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    • v.13 no.3
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    • pp.537-550
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    • 2006
  • In this paper, we develope three modified empirical distribution function type tests, the modified Cramer-von Mises test, the modified Anderson-Darling test, and the modified Kolmogorov-Smirnov test for the two-parameter exponential distribution with unknown parameters based on multiply Type-II censored samples. For each test, Monte Carlo techniques are used to generate the critical values. The powers of these tests are also investigated under several alternative distributions.

Goodness-of-fit tests for the inverse Weibull or extreme value distribution based on multiply type-II censored samples

  • Kang, Suk-Bok;Han, Jun-Tae;Seo, Yeon-Ju;Jeong, Jina
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.4
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    • pp.903-914
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    • 2014
  • The inverse Weibull distribution has been proposed as a model in the analysis of life testing data. Also, inverse Weibull distribution has been recently derived as a suitable model to describe degradation phenomena of mechanical components such as the dynamic components (pistons, crankshaft, etc.) of diesel engines. In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and the shape parameter in the inverse Weibull distribution under multiply type-II censoring. We also develop four modified empirical distribution function (EDF) type tests for the inverse Weibull or extreme value distribution based on multiply type-II censored samples. We also propose modified normalized sample Lorenz curve plot and new test statistic.