• 한국데이터정보과학회:학술대회논문집
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• 2004.10a
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• pp.125-133
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• 2004

In this paper, we derive the approximate maximum likelihood estimators of the scale and location parameters of the skewed exponential 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.

• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.145-156
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• 2005

In this paper, we derive the approximate maximum likelihood estimators (AMLEs) of the scale parameter of the half-logistic distribution based on multiply Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error (MSE) for various censored samples.

• Journal of Industrial Technology
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• v.20 no.A
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• pp.159-167
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• 2000

In the study rainfall frequency analysis attemped the many specific property data record duration it is differance from occur to error-term and probability ditribution of concern manifest. error-term analysis of method are fact sample data using method in other hand it is not appear to be fault that sample data of number to be small random variates. Therefore, day-rainfall data: to randomicity consider of this study sample data to the Monte Carlo method by randomize after data recode duration of form was choice method which compared an assumed maternal distribution from splitting frequency analysis consequence. In the conclusion, frequency analysis of chuncheon region rainfall appeared samll RMSE to the Gamma II distribution. In the rainfall frequency analysis estimate RMSE using random variates great transform, RMSE is appear that return period increasing little by little RMSE incresed and data number incresing to RMSE decreseing.

• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.657-666
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• 2011

In this paper, we derive the maximum likelihood estimator(MLE) and some approximate maximum likelihood estimators(AMLEs) of the scale parameter in an exponentiated half logistic distribution based on progressively Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error(MSE) through a Monte Carlo simulation for various censoring schemes. We also obtain the AMLEs of the reliability function.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.817-826
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• 2007

In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and the location parameter in a generalized extreme value distribution under multiply Type-II censoring by the approximate maximum likelihood estimation method. We compare the proposed estimators in the sense of the mean squared error for various censored samples.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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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.

• 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.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.367-378
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• 2008

In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and the location parameter in a double Rayleigh 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.

• Journal of Korean Society of Forest Science
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• v.61 no.1
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• pp.1-7
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• 1983

In the estimation of diameter distribution in a stand using Weibull distribution function, the calculation method of experimental distribution was presented in previous paper. This study was to estimate the diameter distribution of Korean pine stands by Weibull distribution which represents Gamma function, with mean diameter and mean basal-area diameter of the random sample trees. The results obtained fitted the diameter distribution in experimental stands. Thus, this method appears to be used for the estimation of diameter distribution in a stand as well as for the analysis and prediction of stand construction for the future.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.163-169
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• 2006

This paper deals with the comparison of parameter estimation methods in a 3-parameter Kappa distribution which is sometimes used in flood frequency analysis. The method of moment estimation(MME), L-moment estimation(L-ME), and maximum likelihood estimation(MLE) are applied to estimate three parameters. The performance of these methods are compared by Monte-carlo simulations. Especially for computing MME and L-ME, ike dimensional nonlinear equations are simplied to one dimensional equation which is calculated by the Newton-Raphson iteration under constraint. Based on the criterion of the mean squared error, the L-ME is recommended to use for small sample size $(n\leq100)$ while MLE is good for large sample size.