• 한국학교수학회논문집
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• 제9권3호
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• pp.309-316
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• 2006

이 논문에서는 현재 중등학교 수학의 통계교육에서 다루고 있는 통계용어의 의미상 혼선과 애매한 내용을 수학교사를 대상으로 알아보고, 표본평균의 확률분포에 대한 지도 영역에 있어서 표집(sampling, 표본추출)의 문맥에서 표집오차(sampling error)와 표본평균의 표집분포(sampling distribution)라는 용어를 도입하여 일관성 있게 사용할 것을 제안하였다. 현행 중고등학교의 수학과의 통계의 용어 정의와 개념설명에 있어서, 교육부가 검정한 12종의 검정 교과서와 국정교과서 간에서도 차이는 물론 의미의 혼선과 함께 정의의 일관성의 부족은 통계를 교육하는 수학교사와 학생들에게 심각한 오개념을 형성하게 만들고, 그 애매함으로 인하여 통계학의 학문 자체에 대한 흥미와 태도의 정의적인 면에서 부정적인 영향을 주고 있음이 발견되었다 본 연구에서는 표본평균의 확률분포의 효율적인 지도를 위한 표본오차 대신에 표집오차를 사용할 것과 표집분포의 용어를 도입함으로서 통계용어의 정확한 사용을 동하여 교사와 학생들에게 통계용어의 올바른 개념의 형성과 이해는 물론 통계교육의 일관성과 계열성 유지의 필요성을 제기하였다.

• Journal of the Korean Statistical Society
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• 제33권3호
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• pp.323-337
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• 2004

This article coined a general class of estimators for various measures in normal population when some' a priori' or guessed value of standard deviation a is available in addition to sample information. The class of estimators is primarily defined for a function of standard deviation. An unbiased estimator and the minimum mean squared error estimator are worked out and the suggested class of estimators is compared with these classical estimators. Numerical computations in terms of percent relative efficiency and absolute relative bias established the merits of the proposed class of estimators especially for small samples. Simulation study confirms the excellence of the proposed class of estimators. The beauty of this article lies in estimation of various measures like standard deviation, variance, Fisher information, precision of sample mean, process capability index $C_{p}$, fourth moment about mean, mean deviation about mean etc. as particular cases of the proposed class of estimators.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.647-654
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• 2003

Bayesian probability models for finite populations are considered assuming so-called the super-population. We find the posterior distribution of population mean by a new approach, using the concept of pivotal quantity for the small sample case. A large sample theory is also treated throught the concept of asymptotically pivotal quantity.

• Communications for Statistical Applications and Methods
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• 제4권2호
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• pp.515-522
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• 1997

In this paper, we find the second derivative of mean busy cycle with respect to a parameter of inter-arrival time distribution. We show that this derivative can be estimated from single sample path. We do the similar thing for the mean number of arrivals during busy cycle.

• Journal of the Korean Data and Information Science Society
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• 제13권2호
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• pp.39-44
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• 2002

We compare MISE of the MLE, UMVUE, invariantly optimal estimator and Jacknife estimator for the reliability function of the Weibull distribution when the sample size is small.

• Communications for Statistical Applications and Methods
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• 제12권3호
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• pp.643-652
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• 2005

It has been known that the exponentiated exponential distribution can be used as a possible alternative to the gamma distribution or the Weibull distribution in many situations. But the maximum likelihood method does not admit explicit solutions when the sample is multiply censored. So we derive the approximate maximum likelihood estimators for the location and scale parameters in the exponentiated exponential distribution that are explicit function of order statistics. We also 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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• 제7권2호
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• pp.385-392
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• 2000

Many tests for multivariate normality are based on the spherical coordinates of the scaled residuals of multivariate observations. Moore and Stubblebine's (1981) Pearson chi-square test is based on the radii of the scaled residuals, or equivalently the sample Mahalanobis distances of the observations from the sample mean vector. The chi-square statistic does not have a limiting chi-square distribution since the unknown parameters are estimated from ungrouped data. We will derive a simple closed form of the Rao-Robson chi-square test statistic and provide a self-contained proof that it has a limiting chi-square distribution. We then provide an illustrative example of application to a real data with a simulation study to show the accuracy in finite sample of the limiting distribution.

• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.259-268
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• 2006

For Type-II censored sample, we propose three modified entropy estimators based on the Vasieck's estimator, van Es' estimator, and Correa's estimator. We also propose the goodness-of-fit tests of the Weibull distribution based on the modified entropy estimators. We simulate the mean squared errors (MSE) of the proposed entropy estimators and the powers of the proposed tests. We also compare the proposed tests with the modified Kolmogorov-Smirnov and Cramer-von-Mises tests which were proposed by Kang et al. (2003).

• Communications for Statistical Applications and Methods
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• 제18권5호
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• pp.645-655
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• 2011

Chandrasekar et al. (2004) introduced a generalized Type-II hybrid censoring. In this paper, we propose generalized doubly Type-II hybrid censoring. In addition, this paper presents the statistical inference on the scale parameter for the half logistic distribution when samples are generalized doubly Type-II hybrid censoring. The approximate maximum likelihood(AMLE) method is developed to estimate the unknown parameter. The scale parameter is estimated by the AMLE method using two di erent Taylor series expansion types. We compar the AMLEs in the sense of the mean square error(MSE). The simulation procedure is repeated 10,000 times for the sample size n = 20; 30; 40 and various censored samples. The $AMLE_I$ is better than $AMLE_{II}$ in the sense of the MSE.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2005년도 춘계학술대회
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• pp.59-68
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• 2005

We consider the problem of estimating the scale and shape parameter of the Weibull distribution based on censored samples. we propose the approximate maximum likelihood estimators (AMLEs) of the scale and shape parameters in the Weibull distribution based on Type-II censored samples. We compare the proposed estimators in the sense of mean squared error (MSE).