• Title/Summary/Keyword: distribution parameter

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Robustness of Predictive Density and Optimal Treatment Allocation to Non-Normal Prior for The Mean

  • Bansal, Ashok K.;Sinha, Pankaj
    • Journal of the Korean Statistical Society
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    • v.22 no.2
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    • pp.235-247
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    • 1993
  • The predictive density function of a potential future observation and its first four moments are obtained in this paper to study the effects of a non-normal prior of the unknown mean of a normal population. The derived predictive density function is modified to study changes in utility curves, used to choose the optimum treatment from a given set of treatments, at a given level of stimulus due to slight deviations from normality of the prior distribution. Numerical illustrations are provided to exhibit some effectsl.

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Predictions for Progressively Type-II Censored Failure Times from the Half Triangle Distribution

  • Seo, Jung-In;Kang, Suk-Bok
    • Communications for Statistical Applications and Methods
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    • v.21 no.1
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    • pp.93-103
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    • 2014
  • This paper deals with the problem of predicting censored data in a half triangle distribution with an unknown parameter based on progressively Type-II censored samples. We derive maximum likelihood predictors and some approximate maximum likelihood predictors of censored failure times in a progressively Type-II censoring scheme. In addition, we construct the shortest-length predictive intervals for censored failure times. Finally, Monte Carlo simulations are used to assess the validity of the proposed methods.

Estimation for the Triangular Distribution under Progressive Type-II Censoring

  • Kang, Suk-Bok;Han, Jun-Tae;Jung, Won-Tae
    • Communications for Statistical Applications and Methods
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    • v.15 no.5
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    • pp.765-774
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    • 2008
  • In this paper, we derive the approximate maximum likelihood estimators(AMLEs) and maximum likelihood estimator of the scale parameter in a triangular distribution based on progressive Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error through Monte Carlo simulation for various progressive censoring schemes.

A Closed-Form Bayesian Inferences for Multinomial Randomized Response Model

  • Heo, Tae-Young;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.121-131
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    • 2007
  • In this paper, we examine the problem of estimating the sensitive characteristics and behaviors in a multinomial randomized response model using Bayesian approach. We derived a posterior distribution for parameter of interest for multinomial randomized response model. Based on the posterior distribution, we also calculated a credible intervals and mean squared error (MSE). We finally compare the maximum likelihood estimator and the Bayes estimator in terms of MSE.

Fluid Queueing Model with Fractional Brownian Input

  • Lee, Jiyeon
    • Communications for Statistical Applications and Methods
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    • v.9 no.3
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    • pp.649-663
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    • 2002
  • We consider an unlimited fluid queueing model which has Fractional Brownian motion(FBM) as an input and a single server of constant service rate. By using the result of Duffield and O'Connell(6), we investigate the asymptotic tail-distribution of the stationary work-load. When there are multiple homogeneous FBM inputs, the workload distribution is similar to that of the queue with one FBM input; whereas for the heterogeneous sources the asymptotic work-load distributions is dominated by the source with the largest Hurst parameter.

AMLE for Normal Distribution under Progressively Censored Samples

  • Kang, Suk-Bok;Cho, Young-Suk
    • Journal of the Korean Data and Information Science Society
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    • v.9 no.2
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    • pp.203-209
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    • 1998
  • By assuming a progressively censored sample, we propose the approximate maximum likelihood estimator (AMLE) of the location nd the scale parameters of the two-parameter normal distribution and obtain the asymptotic variances and covariance of the AMLEs. An example is given to illustrate the methods of estimation discussed in this paper.

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Estimation for the Half-Triangle Distribution Based on Progressively Type-II Censored Samples

  • Han, Jun-Tae;Kang, Suk-Bok
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.3
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    • pp.951-957
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    • 2008
  • We derive some approximate maximum likelihood estimators(AMLEs) and maximum likelihood estimator(MLE) of the scale parameter in the half-triangle distribution based on progressively Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples. We also obtain the approximate maximum likelihood estimators of the reliability function using the proposed estimators. We compare the proposed estimators in the sense of the mean squared error.

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Inference on Reliability in an Exponentiated Uniform Distribution

  • Lee, Chang-Soo;Won, Ho-Yon
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.2
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    • pp.507-513
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    • 2006
  • We shall consider an inference of the reliability and an estimation of the right-tail probability in an exponentiated uniform distribution. And we shall compare numerically efficiencies for proposed estimators of the scale parameter and right-tail probability in the small sample sizes.

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A Reliability Analysis on the Fatigue Life Prediction in Carbon/Epoxy Composite Material (Carbon/Epoxy 복합재료의 피로수명예측에 관한 신뢰성 해석)

  • Jang, Seong-Soo
    • Journal of the Korean Society of Industry Convergence
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    • v.10 no.3
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    • pp.143-147
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    • 2007
  • In recents years, the statistical properties has become an important quantity for reliability based design of a component. The effects of the materials and test conditions for parameter estimation in residual strength degradation model are studied in carbon/epoxy laminate. It is shown that the correlation between the experimental results and the theoretical prediction on the fatigue life distribution using the life distribution convergence method is very reasonable.

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