• Title/Summary/Keyword: Statistics data

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ASYMPTOTIC PROPERTIES OF RANDOM CENTRAL ORDER STATISTICS UNDER CONTAMINATION

  • Kim, Sung-Kyun;Kim, Sung-Lai
    • Journal of applied mathematics & informatics
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    • v.8 no.2
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    • pp.627-634
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    • 2001
  • Under contamination, Bahadur representations with a strong remainder term are derived for random central order statistics with a prescribed limiting rank, and asymptotic normalities for these statistics of truncated and contaminated data are proved, with a suitable limiting rank. From these results, an application to the fixed-width confidence interval problem is available.

A Note on Teaching Statistics in The School Class

  • Lee, Sang-Bock;Lee, Dong-Ro
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.2
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    • pp.449-453
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    • 2006
  • In teaching statistics in the secondary school, most math teachers do it and students enjoy it well before 11th grade. But, both of teachers and students feel statistics hard at 11th grade, which has been contained permutations, combinations, random variables, probability distributions, hypotheses and tests for normal distribution. In this study, we explore the efficient teaching methods of statistics for math teachers and also find many students enjoying it.

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Classification of Microarray Gene Expression Data by MultiBlock Dimension Reduction

  • Oh, Mi-Ra;Kim, Seo-Young;Kim, Kyung-Sook;Baek, Jang-Sun;Son, Young-Sook
    • Communications for Statistical Applications and Methods
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    • v.13 no.3
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    • pp.567-576
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    • 2006
  • In this paper, we applied the multiblock dimension reduction methods to the classification of tumor based on microarray gene expressions data. This procedure involves clustering selected genes, multiblock dimension reduction and classification using linear discrimination analysis and quadratic discrimination analysis.

A Study on the Development of Statistics in Korean Medicine (한의약 분야 통계 개선방안에 관한 연구)

  • Kim, Dae-Young;Oh, Yun-Jung;Mun, Hye-Sun;Han, Chang-Yon
    • Korean Journal of Oriental Medicine
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    • v.13 no.1 s.19
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    • pp.125-128
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    • 2007
  • Objective : This study aims to review the current status and problems of Korean Medicine and attempts to come up with the means to present a comprehensive and effective set of statistical data. Methods : We have analyzed the current statistics and tried to show how to establish an effective system to gather and organize statistics related to Korean Medicine, including national surveys by the Ministry of Health and Welfare or other relevant insititutions. Results : The existing statistics in Korean Medicine were established not as a result of national demand based on comprehensive analysis but due to the demand of the government ministries such as the Ministry of Health and Welfare or other relevant institutions. Thus, the statistics have been revealed to possess limitations such as a lack of systemization and consistency. In addition, the statistics analyze only the current industrial status of Korean Medicine, and as a result the information in unable to show systematic data for innovation, which is indispensable for the advancement and development of the Korean Medicine industry. Conclusion : To improve the statistical data in Korean Medicine, the statistics need to get over not only the level of management or regulation in Korean Medicine, but also the production of fragmentary statistics. It has to ultimately reflect the innovative activities in Korean Medicine nationally, and show what we need to advance and develop the industry.

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Comparison of Nonparametric Maximum Likelihood and Bayes Estimators of the Survival Function Based on Current Status Data

  • Kim, Hee-Jeong;Kim, Yong-Dai;Son, Young-Sook
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.111-119
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    • 2007
  • In this paper, we develop a nonparametric Bayesian methodology of estimating an unknown distribution function F at the given survival time with current status data under the assumption of Dirichlet process prior on F. We compare our algorithm with the nonparametric maximum likelihood estimator through application to simulated data and real data.

Hierarchical Bayes Analysis of Longitudinal Poisson Count Data

  • Kim, Dal-Ho;Shin, Im-Hee;Choi, In-Sun
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.2
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    • pp.227-234
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    • 2002
  • In this paper, we consider hierarchical Bayes generalized linear models for the analysis of longitudinal count data. Specifically we introduce the hierarchical Bayes random effects models. We discuss implementation of the Bayes procedures via Markov chain Monte Carlo (MCMC) integration techniques. The hierarchical Baye method is illustrated with a real dataset and is compared with other statistical methods.

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Exploratory Data Analysis for microarray experiments with replicates

  • Lee, Eun-Kyung;Yi, Sung-Gon;Park, Tae-Sung
    • Proceedings of the Korean Statistical Society Conference
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    • 2005.11a
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    • pp.37-41
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    • 2005
  • Exploratory data analysis(EDA) is the initial stage of data analysis and provides a useful overview about the whole microarray experiment. If the experiments are replicated, the analyst should check the quality and reliability of microarray data within same experimental condition before the deeper statistical analysis. We shows EDA method focusing on the quality and reproducibility for replicates.

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Bootstrap Confidence Intervals for the Difference of Quantiles of Right Censored Data

  • Na, Jong-Hwa;Park, Hyo-Il;Jang, Young-Mi
    • Communications for Statistical Applications and Methods
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    • v.11 no.3
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    • pp.447-454
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    • 2004
  • In this paper, we consider the bootstrap method to the interval estimation of the difference of quantiles of right censored data. We showed the validity of bootstrap method and compare with others with real data example. In simulation various resampling schemes for right censored data are also considered.

Robustness, Data Analysis, and Statistical Modeling: The First 50 Years and Beyond

  • Barrios, Erniel B.
    • Communications for Statistical Applications and Methods
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    • v.22 no.6
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    • pp.543-556
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    • 2015
  • We present a survey of contributions that defined the nature and extent of robust statistics for the last 50 years. From the pioneering work of Tukey, Huber, and Hampel that focused on robust location parameter estimation, we presented various generalizations of these estimation procedures that cover a wide variety of models and data analysis methods. Among these extensions, we present linear models, clustered and dependent observations, times series data, binary and discrete data, models for spatial data, nonparametric methods, and forward search methods for outliers. We also present the current interest in robust statistics and conclude with suggestions on the possible future direction of this area for statistical science.

Multivariate Control Charts for Autocorrelated Process

  • Cho, Gyo-Young;Park, Mi-Ra
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.2
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    • pp.289-301
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    • 2003
  • In this paper, we propose Shewhart control chart and EWMA control chart using the autocorrelated data which are common in chemical and process industries and lead to increase the number of false alarms when conventional control charts are applied. The effect of autocorrelated data is modeled as a autoregressive process, and canonical analysis is used to reduce the dimensionality of the data set and find the canonical variables that explain as much of the data variation as possible. Charting statistics are constructed based on the residual vectors from the canonical variables which are uncorrelated over time, and the control charts for these statistics can attenuate the autocorrelation in the process data. The charting procedures are illustrated with a numerical example and simulation is conducted to investigate the performances of the proposed control charts.

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