• 제목/요약/키워드: Approximate Maximum Likelihood Estimator

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Estimation for the extreme value distribution under progressive Type-I interval censoring

  • Nam, Sol-Ji;Kang, Suk-Bok
    • Journal of the Korean Data and Information Science Society
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    • 제25권3호
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    • pp.643-653
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    • 2014
  • In this paper, we propose some estimators for the extreme value distribution based on the interval method and mid-point approximation method from the progressive Type-I interval censored sample. Because log-likelihood function is a non-linear function, we use a Taylor series expansion to derive approximate likelihood equations. We compare the proposed estimators in terms of the mean squared error by using the Monte Carlo simulation.

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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    • 제25권1호
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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.

Estimation of the half-logistic distribution based on multiply Type I hybrid censored sample

  • Shin, Hyejung;Kim, Jungdae;Lee, Changsoo
    • Journal of the Korean Data and Information Science Society
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    • 제25권6호
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    • pp.1581-1589
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    • 2014
  • In this paper, we consider maximum likelihood estimators of the location and scale parameters for the half-logistic distribution when samples are multiply Type I hybrid censored. The scale parameter is estimated by approximate maximum likelihood estimation methods using two different Taylor series expansion types ($\hat{\sigma}_I$, $\hat{\sigma}_{II}$). We compare the estimators in the sense of the root mean square error (RMSE). The simulation procedure is repeated 10,000 times for the sample size n=20 and 40 and various censored schemes. The approximate MLE of the second type is better than that of the first type in the sense of the RMSE. Further an illustrative example with the real data is presented.

Estimation for Exponential Distribution Based on Multiply Type-II Censored Samples

  • 강석복
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2004년도 춘계학술대회
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    • pp.203-210
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    • 2004
  • When the available sample is multiply Type-II censored, the maximum likelihood estimators of the location and the scale parameters of two- parameter exponential distribution do not admit explicitly. In this case, we propose some estimators which are linear functions of the order statistics and also propose some estimators by approximating the likelihood equations appropriately. We compare the proposed estimators by the mean squared errors.

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Estimations in a skewed uniform distribution

  • Son, Hee-Ju;Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
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    • 제20권4호
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    • pp.733-740
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    • 2009
  • We obtain a skewed uniform distribution by a uniform distribution, and evaluate its coeffcient of skewness. And we obtain the approximate maximum likelihood estimator (AML) and moment estimator of skew parameter in the skewed uniform distribution. And we compare simulated mean squared errors (MSE) of those estimators, and also compare MSE of two proposed reliability estimators in two independent skewed uniform distributions each with different skew parameters.

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Estimating a Skewed Parameter and Reliability in a Skew-Symmetric Double Rayleigh Distribution

  • Son, Hee-Ju;Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
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    • 제18권4호
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    • pp.1205-1214
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    • 2007
  • We define a skew-symmetric double Rayleigh distribution by a symmetric double Rayleigh distribution, and derive an approximate maximum likelihood estimator(AML) and a moment estimator(MME) of a skewed parameter in a skew-symmetric double Rayleigh distribution, and hence compare simulated mean squared errors of those two estimators. We also compare simulated mean squared errors of two proposed estimators of reliability in two independent skew-symmetric double Rayleigh distributions.

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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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Estimations in a Skewed Double Weibull Distribution

  • Son, Hee-Ju;Woo, Jung-Soo
    • Communications for Statistical Applications and Methods
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    • 제16권5호
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    • pp.859-870
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    • 2009
  • We obtain a skewed double Weibull distribution by a double Weibull distribution, and evaluate its coefficient of skewness. And we obtain the approximate maximum likelihood estimator(AML) and moment estimator of skew parameter in the skewed double Weibull distribution, and hence compare simulated mean squared errors(MSE) of those estimators. We compare simulated MSE of two proposed reliability estimators in two independent skewed double Weibull distributions each with different skew parameters. Finally we introduce a skewed double Weibull distribution generated by a uniform kernel.

Estimation of the Exponential Distributions based on Multiply Progressive Type II Censored Sample

  • Lee, Kyeong-Jun;Park, Chan-Keun;Cho, Young-Seuk
    • Communications for Statistical Applications and Methods
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    • 제19권5호
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    • pp.697-704
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    • 2012
  • The maximum likelihood(ML) estimation of the scale parameters of an exponential distribution based on progressive Type II censored samples is given. The sample is multiply censored (some middle observations being censored); however, the ML method does not admit explicit solutions. In this paper, we propose multiply progressive Type II censoring. This paper presents the statistical inference on the scale parameter for the exponential distribution when samples are multiply progressive Type II censoring. The scale parameter is estimated by approximate ML methods that use two different Taylor series expansion types ($AMLE_I$, $AMLE_{II}$). We also obtain the maximum likelihood estimator(MLE) of the scale parameter under the proposed multiply progressive Type II censored samples. We compare the estimators in the sense of the mean square error(MSE). The simulation procedure is repeated 10,000 times for the sample size n = 20 and 40 and various censored schemes. The $AMLE_{II}$ is better than MLE and $AMLE_I$ in the sense of the MSE.

감마 일반화 선형 모형에서의 산포 모수 추정량에 대한 효율성 연구 (Comparing the efficiency of dispersion parameter estimators in gamma generalized linear models)

  • 조성일;이우주
    • 응용통계연구
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    • 제30권1호
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    • pp.95-102
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    • 2017
  • 감마 일반화 선형모형은 포아송 분포 또는 이항 분포에 기반한 일반화 선형모형에 비해 적은 관심을 받아왔다. 따라서 감마 일반화 선형모형에서는 오래전에 개발된 통계적인 기법이 아직도 사용되고 있으며, 특히 산포 모수에 대해서는 근사 추정치가 여전히 사용되고 있다. 본 논문에서는 감마 일반화 선형 모형의 산포 모수에 대해 다양한 추정량들을 알아보고 수치 연구를 통해 그들의 효율성을 비교한다. 수치 실험의 결과 최대 가능도 추정량과 Cox-Reid의 수정된 최대 가능도 추정량이 기존의 근사 추정량에 비해 좋은 성능을 보임을 확인하였다.