• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.169-175
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• 2012

The sensitivity of the performance measures such as the mean and the standard deviation of the queue length and the blocking probability with respect to the moments of the service time are numerically investigated. The service time distribution is fitted with phase type(PH) distribution by matching the first three moments of service time and the M/G/c retrial queue is approximated by the M/PH/c retrial queue. Approximations are compared with the simulation results.

• Communications for Statistical Applications and Methods
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• v.23 no.5
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• pp.411-421
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• 2016

Large frequency limiting distributions of two errors in realized covariance are investigated under noisy and non-synchronous high frequency sampling situations. The first distribution characterizes increased variance of the realized covariance due to noise for large frequency and the second distribution characterizes decreased variance of the realized covariance due to discretization for large frequency. The distribution of the combined error enables us to determine the sampling frequency which depends on a nuisance parameter. A consistent estimator of the nuisance parameter is proposed.

• Mycobiology
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• v.38 no.3
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• pp.159-165
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• 2010

We conducted a species diversity study of the hypogeous Ascomycetes of Israel. The hypogeous Ascomycetes in Israel include members of the families Pyronemataceae, Pezizaceae, and Tuberaceae, which are represented by seven species: Hydnocystis piligera, Terfezia arenaria, T. claveryi, T. oligosperma, Tirmania africana, Tuber asa, and T. nitidum; only T. asa is new to Israeli mycobiota. Synonymy, locations, collection data, general distribution, distribution in Israel, descriptions, a key to identification, illustrations, and taxonomic remarks are provided.

• International Journal of Reliability and Applications
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• v.9 no.2
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• pp.153-165
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• 2008

This paper discusses the reliability equivalences of a series-parallel system. The system components are assumed to be independent and identical. The failure rates of the system components are functions of time and follow Weibull distribution. Three different methods are used to improve the given system reliability. The reliability equivalence factor is obtained using the reliability function. The fractiles of the original and improved systems are also obtained. Numerical example is presented to interpret how to utilize the obtained results.

• Journal of applied mathematics & informatics
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• v.35 no.5_6
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• pp.651-657
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• 2017

A sequence {$X_n,\;n{\geq}1$} of independent and identically distributed random variables with absolutely continuous (with respect to Lebesque measure) cumulative distribution function F(x) is considered. We obtain two characterizations of a family of continuous probability distribution by independence property of record values.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.909-917
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• 2003

Although many classification models have been used to classify binary data, none of the classification models dominates all varying circumstances depending on the number of variables and the size of data(Asparoukhov and Krzanowski (2001)). This paper proposes a classification model which uses information on marginal distributions of sub-variables and its maximum entropy distribution. Classification experiments by using simulation are discussed.

• 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.

• 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.15 no.1
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• pp.87-94
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• 2002

Trot(1999) considered how to calculate the expected area of a random triangle in the unit square $[0,1]{\times}[0,1]$. He used the Mathematica software package for the computational part. In this article, we study various aspects of the probability distribution of a triangle randomly chosen inside the circle of radius r. A simulation activity that can be conducted in statistics and probability classrooms is also considered.

• 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.