• Title/Summary/Keyword: distribution parameter

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Estimation for Two-Parameter Rayleigh Distribution Based on Multiply Type-II Censored Sample

  • Han, Jun-Tae;Kang, Suk-Bok
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.4
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    • pp.1319-1328
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    • 2006
  • For multiply Type-II censored samples from two-parameter Rayleigh distribution, the maximum likelihood method does not admit explicit solutions. In this case, we propose some explicit estimators of the location and scale parameters in the Rayleigh distribution by the approximate maximum likelihood methods. We compare the proposed estimators in the sense of the mean squared error for various censored samples.

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A Note on Estimating Parameters in The Two-Parameter Weibull Distribution

  • Rahman, Mezbahur;Pearson, Larry M.
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.4
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    • pp.1091-1102
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    • 2003
  • The Weibull variate is commonly used as a lifetime distribution in reliability applications. Estimation of parameters is revisited in the two-parameter Weibull distribution. The method of product spacings, the method of quantile estimates and the method of least squares are applied to this distribution. A comparative study between a simple minded estimate, the maximum likelihood estimate, the product spacings estimate, the quantile estimate, the least squares estimate, and the adjusted least squares estimate is presented.

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Estimation for scale parameter of type-I extreme value distribution

  • Choi, Byungjin
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.2
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    • pp.535-545
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    • 2015
  • In a various range of applications including hydrology, the type-I extreme value distribution has been extensively used as a probabilistic model for analyzing extreme events. In this paper, we introduce methods for estimating the scale parameter of the type-I extreme value distribution. A simulation study is performed to compare the estimators in terms of mean-squared error and bias, and the obtained results are provided.

On the Effects of Plotting Positions to the Probability Weighted Moments Method for the Generalized Logistic Distribution

  • Kim, Myung-Suk
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.561-576
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    • 2007
  • Five plotting positions are applied to the computation of probability weighted moments (PWM) on the parameters of the generalized logistic distribution. Over a range of parameter values with some finite sample sizes, the effects of five plotting positions are investigated via Monte Carlo simulation studies. Our simulation results indicate that the Landwehr plotting position frequently tends to document smaller biases than others in the location and scale parameter estimations. On the other hand, the Weibull plotting position often tends to cause larger biases than others. The plotting position (i - 0.35)/n seems to report smaller root mean square errors (RMSE) than other plotting positions in the negative shape parameter estimation under small samples. In comparison to the maximum likelihood (ML) method under the small sample, the PWM do not seem to be better than the ML estimators in the location and scale parameter estimations documenting larger RMSE. However, the PWM outperform the ML estimators in the shape parameter estimation when its magnitude is near zero. Sensitivity of right tail quantile estimation regarding five plotting positions is also examined, but superiority or inferiority of any plotting position is not observed.

Parameter Estimation of the Two-Parameter Exponential Distribution under Three Step-Stress Accelerated Life Test

  • Moon, Gyoung-Ae;Kim, In-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.4
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    • pp.1375-1386
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    • 2006
  • In life testing, the lifetimes of test units under the usual conditions are so long that life testing at usual conditions is impractical. Testing units are subjected to conditions of high stress to yield informations quickly. In this paper, the inferences of parameters on the three step-stress accelerated life testing are studied. The two-parameter exponential distribution with a failure rate function that a log-quadratic function of stress and the tempered failure rate model are considered. We obtain the maximum likelihood estimators of the model parameters and their confidence regions. A numerical example will be given to illustrate the proposed inferential procedures.

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Objective Bayesian multiple hypothesis testing for the shape parameter of generalized exponential distribution

  • Lee, Woo Dong;Kim, Dal Ho;Kang, Sang Gil
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.1
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    • pp.217-225
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    • 2017
  • This article deals with the problem of multiple hypothesis testing for the shape parameter in the generalized exponential distribution. We propose Bayesian hypothesis testing procedures for multiple hypotheses of the shape parameter with the noninformative prior. The Bayes factor with the noninformative prior is not well defined. The reason is that the most of the noninformative prior can be improper. Therefore we study the default Bayesian multiple hypothesis testing methods using the fractional and intrinsic Bayes factors with the reference priors. Simulation study is performed and an example is given.

Parameter Estimation and Confidence Limits for the WeibulI Distribution (Weibull 확률분포함수(確率分布函數)의 매개변수(媒介變數) 추정(推定)과 신뢰한계(信賴限界) 유도(誘導))

  • Heo, Jun Haeng
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.13 no.4
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    • pp.141-150
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    • 1993
  • For the three parameter Weibull distribution, the parameter estimation techniques are applied and the asymptotic variances of the quantile to obtain the confidence limits for a given return period are derived. Three estimation techniques are used for these purposes: the methods of moments, maximum likelihood and probability weighted moments. The three parameter Weibull distribution as a flood frequency model is applied to actual flood data.

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Maximum penalized likelihood estimation for a stress-strength reliability model using complete and incomplete data

  • Hassan, Marwa Khalil
    • Communications for Statistical Applications and Methods
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    • v.25 no.4
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    • pp.355-371
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    • 2018
  • The two parameter negative exponential distribution has many practical applications in queuing theory such as the service times of agents in system, the time it takes before your next telephone call, the time until a radioactive practical decays, the distance between mutations on a DNA strand, and the extreme values of annual snowfall or rainfall; consequently, has many applications in reliability systems. This paper considers an estimation problem of stress-strength model with two parameter negative parameter exponential distribution. We introduce a maximum penalized likelihood method, Bayes estimator using Lindley approximation to estimate stress-strength model and compare the proposed estimators with regular maximum likelihood estimator for complete data. We also introduce a maximum penalized likelihood method, Bayes estimator using a Markov chain Mote Carlo technique for incomplete data. A Monte Carlo simulation study is performed to compare stress-strength model estimates. Real data is used as a practical application of the proposed model.

Noninformative priors for the shape parameter in the generalized Pareto distribution

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.1
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    • pp.171-178
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    • 2013
  • In this paper, we develop noninformative priors for the generalized Pareto distribution when the parameter of interest is the shape parameter. We developed the first order and the second order matching priors.We revealed that the second order matching prior does not exist. It turns out that the reference prior satisfies a first order matching criterion, but Jeffrey's prior is not a first order matching prior. Some simulation study is performed and a real example is given.

Statistical Distribution of Fatigue Crack Growth Rate for Friction Stir Welded Joints of Al7075-T651 (Al7075-T651의 마찰교반용접된 접합부의 피로균열전파율의 통계적 분포)

  • Ahn, Seok-Hwan;Kim, Seon-Jin
    • Journal of Power System Engineering
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    • v.17 no.4
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    • pp.86-93
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    • 2013
  • This paper deals with the effects of driving force and material properties on statistical distribution of fatigue crack growth rate (FCGR) for the friction stir welded joints of Al 7075-T651 aluminum plate. In this work, the statistical probability distribution of fatigue crack growth rate was analyzed by using our previous constant stress intensity factor range controlled fatigue crack growth test data. As far as this study are concerned, the statistical probability distribution of fatigue crack growth rate for the friction stir welded (FSWed) joints was found to evaluate the variability of fatigue crack growth rate for base metal (BM), heat affected zone (HAZ) and weld metal (WM) specimens. The probability distribution of fatigue crack growth rate for FSWed joints was found to follow well log-normal distribution. The shape parameter of BM and HAZ was decreased with increasing the driving force, however, the shape parameter of WM was decreased and increased with increasing the driving force. The scale parameter of BM, HAZ and WM was increased with the driving force.