• 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.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.23-32
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• 2007

We consider penalized likelihood regression with data from the negative binomial distribution with unknown shape parameter. Smoothing parameter selection and asymptotically efficient low dimensional approximations are employed for negative binomial data along with shape parameter estimation through several different algorithms.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.713-723
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• 2013

An objective Bayesian estimation procedure of the two-parameter Pareto distribution is presented under the reference prior and the noninformative prior. Bayesian estimators are obtained by Gibbs sampling. The steps to generate parameters in the Gibbs sampler are from the shape parameter of the gamma distribution and then the scale parameter by the adaptive rejection sampling algorism. A numerical study shows that the proposed objective Bayesian estimation outperforms other estimations in simulated bias and mean squared error.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.4
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• pp.346-352
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• 2009

In the present study, the Weibull statistical analysis using the Monte-Carlo simulation has been performed to investigate the micro-Vickers hardness measurement reliability considering the variability. Experimental indentation test were performed with a micro-Vickers hardness tester for as-received and quenching and tempering specimens in SCM440 steels. The distribution of micro-Vickers hardness is found to be 2-parameter Weibull distribution function. The mean values and coefficients of variation (COV) for both data set are compared with results based on Weibull statistical analysis. Finally, Monte-Carlo simulation was performed in order to evaluate the effect of sample size on the micro-Vickers hardness measurement reliability. For the parent distribution with shape parameter 30.0 and scale parameter 200.0 (COV=0.040), the number of sample data required to obtain the true Weibull parameters was founded by 20. For the parent distribution with shape parameter 10.0 and scale parameter 200.0 (COV=0.1240), the number of sample data required to obtain the true Weibull parameters was founded by 30.

• Journal of Environmental Science International
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• v.28 no.1
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• pp.19-35
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• 2019

This study investigates the performance of four Bayesian methods, Random Walk Metropolis (RWM), Hit-And-Run Metropolis (HARM), Adaptive Mixture Metropolis (AMM), and Population Monte Carlo (PMC), for estimating the parameters and uncertainties of probability rainfall distribution, and the results are compared with those of conventional parameter estimation methods; namely, the Method Of Moment (MOM), Maximum Likelihood Method (MLM), and Probability Weighted Method (PWM). As a result, Bayesian methods yield similar or slightly better results in parameter estimations compared with conventional methods. In particular, PMC can reduce parameter uncertainty greatly compared with RWM, HARM, and AMM methods although the Bayesian methods produce similar results in parameter estimations. Overall, the Bayesian methods produce better accuracy for scale parameters compared with the conventional methods and this characteristic improves the accuracy of probability rainfall. Therefore, Bayesian methods can be effective tools for estimating the parameters and uncertainties of probability rainfall distribution in hydrological practices, flood risk assessment, and decision-making support.

• Polymer(Korea)
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• v.38 no.6
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• pp.735-743
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• 2014

The rheological measurement of polypropylene (PP) has been performed using a rheometer, an intrinsic viscometer, and an MI machine to predict the molecular weight and the molecular weight distribution. Also, GPC has been used for the determination of the molecular structure. The distribution broadness parameter using modified Carreau model has been used to make the correlation between the rheological parameter and the molecular structure instead of the rheological PI (polydispersity index) which is determined from the cross of modulus from the dynamic oscillatory measurement. Even though the rheological PI is useful to determine the molecular weight distribution of the PP using controlled rheology, which has narrow and uniform molecular weight distribution, but not suitable to determine the molecular weight distribution of the PP made from direct polymerization which has broad and various molecular weight distribution. However the distribution broadness parameter which determined from the index of the shear thinning of the PP melt well predicts the molecular weight distribution of PP.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.262-267
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• 2001

In this study, the Reliability of degraded steam turbine blade was evaluated using the limited fatigue data. The statistical estimation of limited fatigue data implies that some unknown uncertainties which may be involved in fatigue reliability analysis. Therefore, an appropriate distribution in the fatigue strength was determined by the characteristic distribution - linear correlation coefficient, fatigue physics, error parameter. 3-parameter Weibull distribution is the most appropriate distribution to assume for infinite region. The load applied on the blade is mainly tensile. The maximum Von-Mises stress is 219.4 MPa at the steady state service condition. The failure probability($F_p$) derived from the strength-stress interference model using Monte carlo simulation under variable service condition is 0.25% at the 99.99% confidence level.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1175-1182
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• 2011

In this paper, properties of exact confidence interval and some approximate confidence intervals of hyper-geometric parameter, that is the probability of success p in the population is discussed. Usually, binomial distribution is a well known discrete distribution with abundant usage. Hypergeometric distribution frequently replaces a binomial distribution when it is desirable to make allowance for the finiteness of the population size. For example, an application of the hypergeometric distribution arises in describing a probability model for the number of children attacked by an infectious disease, when a fixed number of them are exposed to it. Exact confidence interval estimation of hypergeometric parameter is reviewed. We consider the approximation of hypergeometirc distribution to the binomial and normal distribution respectively. Approximate confidence intervals based on these approximation are also adequately discussed. The performance of exact confidence interval estimates and approximate confidence intervals of hypergeometric parameter is compared in terms of actual coverage probability by small sample Monte Carlo simulation.

• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.3
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• pp.100-116
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• 1993

It is experienced fact that unreasonable design criterion and unsitable operation management for the agricultural structures including reservoirs based on short terms data of monthly flows have been brought about not only loss of lives, but also enormous property damage. For the solution of this point at issue, this study was conducted to simulate long series of synthetic monthly flows by multi-season first order Markov model with selection of best fitting frequency distribution and to make a comparison of statistical parameters between observed and synthetic flows of six watersheds in Yeong San and Seom Jin river systems. The results obtained through this study can be summarized as follows. 1.Both Gamma and two parameter lognormal distribution were found to be suitable ones for monthly flows in all watersheds by Kolmogorov-Smirnov test while those distributions were judged to be unfitness in Nam Pyeong of Yeong San and Song Jeong and Ab Rog watersheds of Seom Jin river systems in the $\chi$$^2$ goodness of fit test. 2.Most of the arithmetic mean values for synthetic monthly flows simulated by Gamma distribution are much closer to the results of the observed data than those of two parameter lognomal distribution in the applied watersheds. 3.Fluctuation for the coefficient of variation derived by Gamma distribution was shown in general as better agreement with the results of the observed data than that of two parameter lognormal distribution in the applied watersheds both in Yeong San and Seom Jin river systems. Especially, coefficients of variation calculated by Gamma distribution are seemed to be much closer to those of the observed data during July and August. 4.It can be concluded that synthetic monthly flows simulated by Gamma distribution are seemed to be much closer to the observed data than those by two parameter lognormal distribution in the applied watersheds. 5.It is to be desired that multi-season first order Markov model based on Gamma distribution which is confirmed as a good fitting one in this study would be compared with Harmonic synthetic model as a continuation follows.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.719-731
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• 2009

This paper deals with properties of the exponentiated extreme value distribution. We derive the approximate maximum likelihood estimators of the scale parameter and location parameter of the exponentiated extreme value distribution based on multiply Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples.