• Title/Summary/Keyword: Limiting conditional distribution

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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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    • v.17 no.4
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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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A Test for Multivariate Normality Focused on Elliptical Symmetry Using Mahalanobis Distances

  • Park, Cheol-Yong
    • 한국데이터정보과학회:학술대회논문집
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    • 2006.04a
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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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A Simple Chi-squared Test of Multivariate Normality Based on the Spherical Data

  • Park, Cheolyong
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.117-126
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    • 2001
  • We provide a simple chi-squared test of multivariate normality based on rectangular cells on the spherical data. This test is simple since it is a direct extension of the univariate chi-squared test to multivariate case and the expected cell counts are easily computed. We derive the limiting distribution of the chi-squared statistic via the conditional limit theorems. We study the accuracy in finite samples of the limiting distribution and then compare the poser of our test with those of other popular tests in an application to a real data.

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The Bahadur Efficiency of the Power-Divergence Statistics Conditional on Margins for Testing homogeneity with Equal Sample Size

  • Kang, Seung-Ho
    • Journal of the Korean Statistical Society
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    • v.26 no.4
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    • pp.453-465
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    • 1997
  • The family of power-divergence statistics conditional on margins is considered for testing homogeneity of .tau. multinomial populations with equal sample size and the exact Bahadur slope is obtained. It is shown that the likelihood ratio test conditional on margins is the most Bahadur efficient among the family of power-divergence statistics.

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The Chi-squared Test of Independence for a Multi-way Contingency Table wish All Margins Fixed

  • Park, Cheolyong
    • Journal of the Korean Statistical Society
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    • v.27 no.2
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    • pp.197-203
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    • 1998
  • To test the hypothesis of complete or total independence for a multi-way contingency table, the Pearson chi-squared test statistic is usually employed under Poisson or multinomial models. It is well known that, under the hypothesis, this statistic follows an asymptotic chi-squared distribution. We consider the case where all marginal sums of the contingency table are fixed. Using conditional limit theorems, we show that the chi-squared test statistic has the same limiting distribution for this case.

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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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    • v.28 no.4
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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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Conditional Bootstrap Methods for Censored Survival Data

  • Kim, Ji-Hyun
    • Journal of the Korean Statistical Society
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    • v.24 no.1
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    • pp.197-218
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    • 1995
  • We first consider the random censorship model of survival analysis. Efron (1981) introduced two equivalent bootstrap methods for censored data. We propose a new bootstrap scheme, called Method 3, that acts conditionally on the censoring pattern when making inference about aspects of the unknown life-time distribution F. This article contains (a) a motivation for this refined bootstrap scheme ; (b) a proof that the bootstrapped Kaplan-Meier estimatro fo F formed by Method 3 has the same limiting distribution as the one by Efron's approach ; (c) description of and report on simulation studies assessing the small-sample performance of the Method 3 ; (d) an illustration on some Danish data. We also consider the model in which the survival times are censered by death times due to other caused and also by known fixed constants, and propose an appropriate bootstrap method for that model. This bootstrap method is a readily modified version of the Method 3.

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Board Gender Diversity and Firm Financial Performance Dispersion: Evidence from the Middle East

  • HABASH, Nojoud;ABUZAROUR, Bashar
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.3
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    • pp.365-375
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    • 2022
  • This study examines the relationship between board gender diversity and financial performance. The annual data of Palestinian nonfinancial listed enterprises from 2015 to 2019 was analyzed using a longitudinal panel analysis for the study's purposes. When conditional mean regression methodologies were used in the study, the results indicate that there is an insignificant relation between board gender diversity and firm financial performance. However, when analyzing women directors' effect on a firm's financial performance, endogeneity is always a concern, therefore, we test for endogeneity by employing the Darbin-Wu Housman test and then by using 2SLS. Nevertheless, when looking at the dispersion of a firm's performance using quantile regression, the results show that having women on the board improves financial performance slightly, especially for high-financial-performing firms. The findings indicate that there is a legal significant gap hindering the protection of gender diversity in boardrooms, and limiting the existence and representation of women in leadership positions, specifically, board of directors. The results of this study contribute to corporate governance and business culture literature by shedding the light on the importance of board gender diversity, to improve the firm financial performance, and hence, protect the interests of all shareholders' categories.