• 제목/요약/키워드: Statistic Analysis

검색결과 984건 처리시간 0.023초

A note on Box-Cox transformation and application in microarray data

  • Rahman, Mezbahur;Lee, Nam-Yong
    • Journal of the Korean Data and Information Science Society
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    • 제22권5호
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    • pp.967-976
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    • 2011
  • The Box-Cox transformation is a well known family of power transformations that brings a set of data into agreement with the normality assumption of the residuals and hence the response variable of a postulated model in regression analysis. Normalization (studentization) of the regressors is a common practice in analyzing microarray data. Here, we implement Box-Cox transformation in normalizing regressors in microarray data. Pridictabilty of the model can be improved using data transformation compared to studentization.

신경 회로망을 이용한 계통 한계비용 예측 (SMP Forecasting Using Artificial Neural Networks)

  • 이정규;김민수;박종배;신중린
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 하계학술대회 논문집 A
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    • pp.389-391
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    • 2002
  • This paper presents the System Marginal Price(SMp) forecasting implementation using backpropagation Neural Networks in Competitive Electricity Market. SMP is very important term to seek the maximum profit to bidding participants. Demand and SMP that necessary data for training Neural Networks, supplied from Korea Power Exchange(KPX). Statistic analysis about predicted SMP presents a part of consideration in end of this paper.

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Deciding a sampling length for estimating the parameters in Geometric Brownian Motion

  • Song, Jun-Mo
    • Journal of the Korean Data and Information Science Society
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    • 제22권3호
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    • pp.549-553
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    • 2011
  • In this paper, we deal with the problem of deciding the length of data for estimating the parameters in geometric Brownian motion. As an approach to this problem, we consider the change point test and introduce simple test statistic based on the cumulative sum of squares test (cusum test). A real data analysis is performed for illustration.

Order identification of transfer function-noise model

  • Park, Seongju;Bae, Hankyung;Huh, Kyungmoo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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    • pp.164-169
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    • 1992
  • Classical methods for estimating transfer function models have not always been successful. A statistic approach to the identification of transfer function models which is corrupted by disturbances or noise is presented. The estimated impulse response is obtained from the autocorrelation function and cross correlation function between the measured input and output. Several data analysis tools such as R- , S- and GPAC array for the estimated impulse response give us pretty clear information on the order of transfer function models.

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Rank Tests for Multivariate Linear Models in the Presence of Missing Data

  • Lee, Jae-Won;David M. Reboussin
    • Journal of the Korean Statistical Society
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    • 제26권3호
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    • pp.319-332
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    • 1997
  • The application of multivariate linear rank statistics to data with item nonresponse is considered. Only a modest extension of the complete data techniques is required when the missing data may be thought of as a random sample, and an appropriate modification of the covariances is derived. A proof of the asymptotic multivariate normality is given. A review of some related results in the literature is presented and applications including longitudinal and repeated measures designs are discussed.

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A Necessity of Measurement Customer Satisfaction to NSO Products for Enhancing Quality

  • Choi, Kyung-Ho
    • Journal of the Korean Data and Information Science Society
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    • 제16권4호
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    • pp.781-790
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    • 2005
  • Nowaday, statistical data with coherence, accuracy and timeliness are necessary to government, company and research center for decision making or research. In other words, the importance of statistical data quality is steadily increasing. Thus, in this paper, we suggest necessity of measuring customer satisfaction with NSO products for enhancing quality. And we construct measurement scale for measuring customer satisfaction based on the statistical quality indicators. Also we advise use of structural equation model in relation analysis for statistic quality elevation.

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MULTIVARIATE JOINT NORMAL LIKELIHOOD DISTANCE

  • Kim, Myung-Geun
    • Journal of applied mathematics & informatics
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    • 제27권5_6호
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    • pp.1429-1433
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    • 2009
  • The likelihood distance for the joint distribution of two multivariate normal distributions with common covariance matrix is explicitly derived. It is useful for identifying outliers which do not follow the joint multivariate normal distribution with common covariance matrix. The likelihood distance derived here is a good ground for the use of a generalized Wilks statistic in influence analysis of two multivariate normal data.

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On Bootstrapping; Bartlett Adjusted Empirical Likelihood Ratio Statistic in Regression Analysis

  • Woochul Kim;Duk-Hyun Ko;Keewon Lee
    • Journal of the Korean Statistical Society
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    • 제25권2호
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    • pp.205-216
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    • 1996
  • The bootstrap calibration method for empirical likelihood is considered to make a confidence region for the regression coefficients. Asymptotic properties are studied regarding the coverage probability. Small sample simulation results reveal that the bootstrap calibration works quite well.

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A Family of Tests for Trend Change in Mean Residual Life with Known Change Point

  • Na, Myung-Hwan;Kim, Jae-Joo
    • Communications for Statistical Applications and Methods
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    • 제7권3호
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    • pp.789-798
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    • 2000
  • The mean residual function is the expected remaining life of an item at age x. The problem of trend change in the mean residual life is great interest in the reliability and survival analysis. In this paper, we develop a family of test statistics for testing whether or not the mean residual life changes its trend. The asymptotic normality of the test statistics is established. Monte Carlo simulations are conducted to study the performance of our test statistics.

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Multicollinarity in Logistic Regression

  • Jong-Han lee;Myung-Hoe Huh
    • Communications for Statistical Applications and Methods
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    • 제2권2호
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    • pp.303-309
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    • 1995
  • Many measures to detect multicollinearity in linear regression have been proposed in statistics and numerical analysis literature. Among them, condition number and variance inflation factor(VIF) are most popular. In this study, we give new interpretations of condition number and VIF in linear regression, using geometry on the explanatory space. In the same line, we derive natural measures of condition number and VIF for logistic regression. These computer intensive measures can be easily extended to evaluate multicollinearity in generalized linear models.

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