• 제목/요약/키워드: chi Method

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Chi-squared Tests for Homogeneity based on Complex Sample Survey Data Subject to Misclassification Error

  • Heo, Sunyeong
    • Communications for Statistical Applications and Methods
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    • 제9권3호
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    • pp.853-864
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    • 2002
  • In the analysis of categorical data subject to misclassification errors, the observed cell proportions are adjusted by a misclassification probabilities and estimates of variances are adjusted accordingly. In this case, it is important to determine the extent to which misclassification probabilities are homogeneous within a population. This paper considers methods to evaluate the power of chi-squared tests for homogeneity with complex survey data subject to misclassification errors. Two cases are considered: adjustment with homogeneous misclassification probabilities; adjustment with heterogeneous misclassification probabilities. To estimate misclassification probabilities, logistic regression method is considered.

Comparison of Parameter Estimation Methods in the Analysis of Multivariate Categorical Data with Logit Models

  • Song, Hae-Hiang
    • Journal of the Korean Statistical Society
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    • 제12권1호
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    • pp.24-35
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    • 1983
  • In fitting models to data, selection of the most desirable estimation method and determination of the adequacy of fitted model are the central issues. This paper compares the maximum likelihood estimators and the minimum logit chi-square estimators, both being best asymptotically normal, when logit models are fitted to infant mortality data. Chi-square goodness-of-fit test and likelihood ratio one are also compared. The analysis infant mortality data shows that the outlying observations do not necessarily result in the same impact on goodness-of-fit measures.

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A Note on the Chi-Square Test for Multivariate Normality Based on the Sample Mahalanobis Distances

  • Park, Cheolyong
    • Journal of the Korean Statistical Society
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    • 제28권4호
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    • pp.479-488
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    • 1999
  • Moore and Stubblebine(1981) suggested a chi-square test for multivariate normality based on cell counts calculated from the sample Mahalanobis distances. They derived the limiting distribution of the test statistic only when equiprobable cells are employed. Using conditional limit theorems, we derive the limiting distribution of the statistic as well as the asymptotic normality of the cell counts. These distributions are valid even when equiprobable cells are not employed. We finally apply this method to a real data set.

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A Test for Multivariate Normality Focused on Elliptical Symmetry Using Mahalanobis Distances

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
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    • 제17권4호
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    • pp.1191-1200
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    • 2006
  • A chi-squared test of multivariate normality is suggested which is mainly focused on detecting deviations from elliptical symmetry. This test uses Mahalanobis distances of observations to have some power for deviations from multivariate normality. We derive the limiting distribution of the test statistic by a conditional limit theorem. A simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we compare the power of our method with those of other popular tests of multivariate normality under two non-normal distributions.

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An Adaptive Test for Ordered Interqartile Ranges among Several Distributions

  • Park, Chul-Gyu
    • Journal of the Korean Statistical Society
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    • 제30권1호
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    • pp.63-76
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    • 2001
  • An adaptive estimation and testing method is proposed for comparing dispersions among several ordered groups. Based upon the large sampling theory for nonparametric quartile estimators, we derive the order restricted estimators and construct a simple test statistic. This test statistic has a mixture of several chi-square distributions as its asymptotic null distribution. The proposed test is illustratively applied to survival time data for the patients with carcinoma of the oropharynx.

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A Test for Multivariate Normality Focused on Elliptical Symmetry Using Mahalanobis Distances

  • 박철용
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
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    • pp.203-212
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    • 2006
  • A chi-squared test of multivariate normality is suggested which is mainly focused on detecting deviations from elliptical symmetry. This test uses Mahalanobis distances of observations to have some power for deviations from multivariate normality. We derive the limiting distribution of the test statistic by a conditional limit theorem. A simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we compare the power of our method with those of other popular tests of multivariate normality under two non-normal distributions.

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New Structure to Enhance the Light Efficiency in LCoS Optical Engine

  • Huang, Chi-Wei;Mo, Chi-Neng;Wu, Shih-Min
    • 한국정보디스플레이학회:학술대회논문집
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    • 한국정보디스플레이학회 2005년도 International Meeting on Information Displayvol.I
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    • pp.744-747
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    • 2005
  • The exploitable efficiency of UHP is very important in a projection system. We always use lens array for light shaping and energy distribution transformation in conventional projection system. Because of the limitation of arc gap and F/# of elements, the utilize efficiency is always dismal. In this paper we try to bring out a new method to reduce the sparkle formed on the PS converter and enhance the system efficiency.

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A Test of Multivariate Normality Oriented for Testing Elliptical Symmetry

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
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    • 제17권1호
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    • pp.221-231
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    • 2006
  • A chi-squared test of multivariate normality is suggested which is oriented for detecting deviations from elliptical symmetry. We derive the limiting distribution of the test statistic via a central limit theorem on empirical processes. A simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we compare the power of our method with those of other popular tests of multivariate normality under a non-normal distribution.

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AN ABS ALGORITHM FOR SOLVING SINGULAR NONLINEAR SYSTEMS WITH RANK ONE DEFECT

  • Ge, Ren-Dong;Xia, Zun-Quan
    • Journal of applied mathematics & informatics
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    • 제9권1호
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    • pp.167-183
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    • 2002
  • A modified discretization ABS algorithm for solving a class of singular nonlinear systems, F($\chi$)=0, where $\chi$, F $\in$ $R^n$, is presented, constructed by combining a discretization ABS algorithm arid a method of Hoy and Schwetlick (1990). The second order differential operation of F at a point is not required to be calculated directly in this algorithm. Q-quadratic convergence of this algorithm is given.