• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1199-1206
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• 2009

This paper deals with the estimation based on progressive Type-II censored samples from the double Rayleigh distribution. We derive some estimators of the location and scale parameters of the double Rayleigh distribution based on progressive 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.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.

• Journal of the Korean Data and Information Science Society
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• v.6 no.2
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• pp.41-50
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• 1995

In this paper, an iterative procedure, which detects the location of the outliers and the joint estimates of the outliers effects and the model parameters in the autoregressive moving average model with two types of outliers, is proposed. The performance of the procedure is compared with the one in Chen and Liu(1993) through the Monte Carlo simulation. The proposed procedure is very robust in the sense that applies the procedures to the stationary time series model with any types of outliers.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.57-64
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• 2000

By assuming a Type-I censored sample, we propose the approximate maximum likelihood estimators(AMLE) of the scale and location parameters of the gamma distribution. We compare the proposed estimators with the maximum likelihood estimators(MLE) in the sense of the mean squared errors(MSE) through Monte Carlo method.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.109-114
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• 2003

The concept of dispersion is intrinsic to the theory and practice of statistics. A formulation of the concept of dispersion can be obtained by comparing the probability of intervals centered about a location parameter, which is peakedness ordering introduced first by Birnbaum (1948). We consider statistical inference concerning peakedness ordering between two arbitrary distributions. We propose nonparametric maximum likelihood estimator of two distributions under peakedness ordering and a likelihood ratio test for equality of dispersion in the sense of peakedness ordering.

• 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.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.209-217
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• 2001

We obtain the approximate maximum likelihood estimators (AMLEs) for the scale and location parameters $\theta$ and $\mu$ in the three-parameter Weibull distribution based on Type-II censored samples. We also compare the AMLEs with the modified maximum likelihood estimators (MMLEs) in the sense of the mean squared error (MSE) based on complete sample.

• Journal of the Korean Statistical Society
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• v.33 no.3
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• pp.303-312
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• 2004

The concept of dispersion is intrinsic to the theory and practice of statistics. A formulation of the concept of dispersion can be obtained by comparing the probability of intervals centered about a location parameter. This is the peakedness ordering introduced first by Birnbaum (1948). We consider statistical inference concerning peakedness ordering between two arbitrary distributions. We propose non parametric maximum likelihood estimators of two distributions under peakedness ordering and a likelihood ratio test for equality of dispersion in the sense of peakedness ordering.

• Journal of the Korean Data and Information Science Society
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• v.11 no.2
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• pp.181-188
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• 2000

The shape of an M-estimation function is generally determined in the sense of either/both maximizing efficiency of an M-estimator at the model or/and bounding the influence function of an M-estimator. We propose an empirical method of choosing a value of the bending constant in Huber's ${\psi}-function$, which is the most widely used M-estimation function when estimating the location parameter.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.183-195
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• 2006

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