• Title/Summary/Keyword: statistics department

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On a Nonparametric Test for Parallelism against Ordered Alternatives

  • Song, Moon Sup;Kim, Jaehee;Jean, Jong Woo;Park, Changsoon
    • Journal of Korean Society for Quality Management
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    • v.17 no.2
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    • pp.70-80
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    • 1989
  • A nonparametric test for testing the parallelism of regression lines against ordered alternatives is proposed. The proposed test statistic is based on a linear combination of robust slope estimators. It is a modified version of the Adichie's test statistics based on scores. A snail-sample Monte Carlo study shows that the proposed test is compatible with the Adichie's test.

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Circular Statistics in Musicology

  • Lee, Jeong-Ran;Oh, Hee-Seok
    • Communications for Statistical Applications and Methods
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    • v.15 no.2
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    • pp.273-282
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    • 2008
  • An essential aspect of music is structure. Beran (2004) introduced a method of comparing piano plays via circular statistics based on the fact that there is circular structure in music. We expand the application of this method to a pair of two pop songs and discuss the possibility of applying it to detecting musical plagiarism. Circular statistics provides an objective view point comparing the musical works.

Moments of Order Statistics from Doubly Truncated Linear-Exponential Distribution

  • Saran, Jagdish;Pushkarna, Narinder
    • Journal of the Korean Statistical Society
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    • v.28 no.3
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    • pp.279-296
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    • 1999
  • In this paper we establish some recurrence relations for both single and product moments of order statistics from a doubly truncated linear- exponential distribution with increasing hazard rate. These recurrence relations would enable one to compute all the higher order moments of order statistics for all sample sizes from those of the lower order in a simple recursive way. In addition, percentage points of order statistics are also discussed. These generalize the corresponding results for the linear- exponential distribution with increasing hazard rate derived by Balakrishnan and Malik(1986)

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On Distribution of Order Statistics from Kumaraswamy Distribution

  • Garg, Mridula
    • Kyungpook Mathematical Journal
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    • v.48 no.3
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    • pp.411-417
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    • 2008
  • In the present paper we derive the distribution of single order statistics, joint distribution of two order statistics and the distribution of product and quotient of two order statistics when the independent random variables are from continuous Kumaraswamy distribution. In particular the distribution of product and quotient of extreme order statistics and consecutive order statistics have also been obtained. The method used is based on Mellin transform and its inverse.

Churn Analysis for the First Successful Candidates in the Entrance Examination for K University

  • Kim, Kyu-Il;Kim, Seung-Han;Kim, Eun-Young;Kim, Hyun;Yang, Jae-Wan;Cho, Jang-Sik
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.1
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    • pp.1-10
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    • 2007
  • In this paper, we focus on churn analysis for the first successful candidates in the entrance examination on 2006 year using Clementine, data mining tool. The goal of this study is to apply decision tree including C5.0 and CART algorithms, neural network and logistic regression techniques to predict a successful candidate churn. And we analyze the churning and nochurning successful candidates and why the successful candidates churn and which successful candidates are most likely to churn in the future using data from entrance examination data of K university on 2006 year.

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Goodness of Fit Test of Normality Based on Kullback-Leibler Information

  • Kim, Jong-Tae;Lee, Woo-Dong;Ko, Jung-Hwan;Yoon, Yong-Hwa;Kang, Sang-Gil
    • Communications for Statistical Applications and Methods
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    • v.6 no.3
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    • pp.909-918
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    • 1999
  • Arizono and Ohta(1989) studied goodness of fit test of normality using the entropy estimator proposed by Vasicek (1976) Recently van Es(1992) and Correa(1995) proposed an estimator of entropy. In this paper we propose goodness of fit test statistics for normality based on Vasicek ven Es and Correa. And we compare the power of the proposed test statistics with Kolmogorov-Smirnov Kuiper Cramer von Mises Watson Anderson-Darling and Finkelstein and Schefer statistics.

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