• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.603-613
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• 2005

We propose some estimators of the location parameter and derive the approximate maximum likelihood estimators (AMLEs) of the scale parameter in the exponential distribution based on multiply Type-II censored samples. We calculate the moments for the proposed estimators of the location parameter, and the AMLEs which are the linear functions of the order statistics. We compare the proposed estimators in the sense of the mean squared error (MSE) for various censored samples.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.989-995
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• 2003

Inference for probability P(Y

• Journal of the Chungcheong Mathematical Society
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• v.22 no.2
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• pp.149-153
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• 2009

Let {$X_{n},\;n\;\geq\;1$} be a sequence of independent and identically distributed random variables with absolutely continuous cumulative distribution function (cdf) F(x) and probability density function (pdf) f(x). Suppose $X_{U(m)},\;m = 1,\;2,\;{\cdots}$ be the upper record values of {$X_{n},\;n\;\geq\;1$}. It is shown that the linearity of the conditional expectation of $X_{U(n+2)}$ given $X_{U(n)}$ characterizes the lomax, exponential and pareto distributions.

• 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.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.203-210
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• 2004

When the available sample is multiply Type-II censored, the maximum likelihood estimators of the location and the scale parameters of two- parameter exponential distribution do not admit explicitly. In this case, we propose some estimators which are linear functions of the order statistics and also propose some estimators by approximating the likelihood equations appropriately. We compare the proposed estimators by the mean squared errors.

• Journal of applied mathematics & informatics
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• v.5 no.1
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• pp.213-222
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• 1998

In this paper we propose several estimators of Gini index of the two-parameter exponential distribution and obtain dis-tributions and moments of the proposed estimators. The proposed estimators are shown to cosistency and will be compares in terms of the proposed estimators. The proposed estimators are shown to cosistency and will be compared in terms of the mean squared error (MSE) through Monte Carlo method.

• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.115-126
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• 2005

In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and location parameter of the double exponential distribution based on 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.9 no.1
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• pp.71-76
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• 1998

By assuming a general progressive Type-II censored sample, we propose the minimum risk estimator (MRE) of the location parameter and the scale parameter of the two-parameter exponential distribution. An example is given to illustrate the methods of estimation discussed in this paper.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1217-1222
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• 2011

In this paper, we show that any circular density can be closely approximated by an exponential family of distributions. Therefore we propose an exponential family of distributions as a new family of circular distributions, which is absolutely suitable to model any shape of circular distributions. In this family of circular distributions, the trigonometric moments are found to be the uniformly minimum variance unbiased estimators (UMVUEs) of the parameters of distribution. Simulation result and goodness of fit test using an asymmetric real data set show usefulness of the novel circular distribution.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.79-90
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• 2019

This study aims to develop time headway distribution models of bicycle traffic flow in a uninterrupted bikeway. The sample data were collected and classified into two groups of traffic volume levels. The lower level traffic volume is defined to be under 8 bicycles per minute, and the higher one is greater or equal to 8 bicycles per minute. The data aggregation interval size was set to be 0.5-second. Four distribution models including normal distribution, negative exponential distribution, shifted negative exponential distribution, and Pearson III distribution were tested, and Chi-square test results shows that the negative exponential distribution and the shifted negative exponential distribution are well fitted to the sample data. Another test results with different sample data also shows the same conclusion.