The Experts below are selected from a list of 8463 Experts worldwide ranked by ideXlab platform
Yongzhao Shao - One of the best experts on this subject based on the ideXlab platform.
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On Rotational Robustness of Shapiro-Wilk Type Tests for Multivariate Normality
Open Journal of Statistics, 2014Co-Authors: Richie Lee, Meng Qian, Yongzhao ShaoAbstract:The Shapiro-Wilk test (SWT) for Normality is well known for its competitive power against numerous one-dimensional alternatives. Several extensions of the SWT to multi-dimensions have also been proposed. This paper investigates the relative strength and rotational robustness of some SWT-based Normality tests. In particular, the Royston’s H-test and the SWT-based test proposed by Villase?or-Alva and Gonzalez-Estrada have R packages available for testing Multivariate Normality; thus they are user friendly but lack of rotational robustness compared to the test proposed by Fattorini. Numerical power comparison is provided for illustration along with some practical guidelines on the choice of these SWT-type tests in practice.
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Notes: A characterization of Multivariate Normality through univariate projections
Journal of multivariate analysis, 2010Co-Authors: Yongzhao Shao, Ming ZhouAbstract:This paper introduces a new characterization of Multivariate Normality of a random vector based on univariate Normality of linear combinations of its components.
Julie Mcivor - One of the best experts on this subject based on the ideXlab platform.
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Testing the Multivariate Normality of Australian Stock Returns
Australian Journal of Management, 1998Co-Authors: Philip Gray, Egon Kalotay, Julie McivorAbstract:The Multivariate Normality of stock returns is a crucial assumption in many tests of assets pricing models. While past Australian research has examined the univariate Normality of returns, univariate test statistics are unreliable for testing Multivariate Normality since they ignore the contemporaneous correlation between asset returns. This paper utilises a Multivariate test procedure, based on the generalised method of moments, to test whether residuals from market model regressions are Multivariate normal. The results suggest violations of the Multivariate Normality assumption which cast doubt over the validity over inferential procedures commonly used in the extant empirical literature.
Kazuyuki Koizumi - One of the best experts on this subject based on the ideXlab platform.
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a monte carlo comparison of jarque bera type tests and henze zirkler test of Multivariate Normality
Communications in Statistics - Simulation and Computation, 2018Co-Authors: Zofia Hanusz, Takashi Seo, Rie Enomoto, Kazuyuki KoizumiAbstract:In the paper, tests for Multivariate Normality (MVN) of Jarque-Bera type, based on skewness and kurtosis, have been considered. Tests proposed by Mardia and Srivastava, and the combined tests based...
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A Monte Carlo comparison of Jarque–Bera type tests and Henze–Zirkler test of Multivariate Normality
Communications in Statistics - Simulation and Computation, 2017Co-Authors: Zofia Hanusz, Takashi Seo, Rie Enomoto, Kazuyuki KoizumiAbstract:In the paper, tests for Multivariate Normality (MVN) of Jarque-Bera type, based on skewness and kurtosis, have been considered. Tests proposed by Mardia and Srivastava, and the combined tests based...
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Modified Jarque-Bera Type Tests for Multivariate Normality in a High-Dimensional Framework
Journal of Statistical Theory and Practice, 2014Co-Authors: Kazuyuki Koizumi, Masashi Hyodo, Tatjana PavlenkoAbstract:In this article, we introduce two types of new omnibus procedures for testing Multivariate Normality based on the sample measures of Multivariate skewness and kurtosis. These characteristics, initially introduced by, for example, Mardia (1970) and Srivastava (1984), were then extended by Koizumi, Okamoto, and Seo (2009), who proposed the Multivariate Jarque–Bera type test () based on the Srivastava (1984) principal components measure scores of skewness and kurtosis. We suggest an improved MJB test () that is based on the Wilson–Hilferty transform, and a modified MJB test () that is based on the F-approximation to . Asymptotic properties of both tests are examined, assuming that both dimensionality and sample size go to infinity at the same rate. Our simulation study shows that the suggested test outperforms both and for a number of high-dimensional scenarios. The test is then used for testing Multivariate Normality of the real data digitalized character image.
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ON JARQUE-BERA TESTS FOR ASSESSING Multivariate Normality
2009Co-Authors: Kazuyuki Koizumi, Naoya Okamoto, Takashi SeoAbstract:In this paper, we consider some tests for the Multivariate Normality based on the sample measures of Multivariate skewness and kurtosis. Sample measures of Multivariate skewness and kurtosis were defined by Mardia [3], Srivastava [9] and so on. We derive new Multivariate Normality tests by using Mardia’s and Srivastava’s moments. For univariate case, Jarque and Bera [1] proposed bivariate test using skewness and kurtosis. We propose some new bivariate tests for assessing Multivariate Normality which are natural extensions of Jarque-Bera test. Finally, the numerical results by Monte Carlo simulation are shown in order to evaluate accuracy of expectations, variances and upper percentage points for new test statistics proposed in this paper.
Zofia Hanusz - One of the best experts on this subject based on the ideXlab platform.
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Multivariate Normality test using normalizing transformation for mardia s Multivariate kurtosis
Communications in Statistics - Simulation and Computation, 2020Co-Authors: Rie Enomoto, Zofia Hanusz, Ayako Hara, Takashi SeoAbstract:AbstractMultivariate skewness and kurtosis were defined by Mardia. However, the distribution of Multivariate Normality test statistics based on skewness and kurtosis is only obtainable for large sa...
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Multivariate Normality test using normalizing transformation for Mardia’s Multivariate kurtosis
Communications in Statistics - Simulation and Computation, 2019Co-Authors: Rie Enomoto, Zofia Hanusz, Ayako Hara, Takashi SeoAbstract:AbstractMultivariate skewness and kurtosis were defined by Mardia. However, the distribution of Multivariate Normality test statistics based on skewness and kurtosis is only obtainable for large sa...
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a monte carlo comparison of jarque bera type tests and henze zirkler test of Multivariate Normality
Communications in Statistics - Simulation and Computation, 2018Co-Authors: Zofia Hanusz, Takashi Seo, Rie Enomoto, Kazuyuki KoizumiAbstract:In the paper, tests for Multivariate Normality (MVN) of Jarque-Bera type, based on skewness and kurtosis, have been considered. Tests proposed by Mardia and Srivastava, and the combined tests based...
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A Monte Carlo comparison of Jarque–Bera type tests and Henze–Zirkler test of Multivariate Normality
Communications in Statistics - Simulation and Computation, 2017Co-Authors: Zofia Hanusz, Takashi Seo, Rie Enomoto, Kazuyuki KoizumiAbstract:In the paper, tests for Multivariate Normality (MVN) of Jarque-Bera type, based on skewness and kurtosis, have been considered. Tests proposed by Mardia and Srivastava, and the combined tests based...
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New tests for Multivariate Normality based on Small's and Srivastava's graphical methods
Journal of Statistical Computation and Simulation, 2012Co-Authors: Zofia Hanusz, Joanna TarasińskaAbstract:In this paper, we propose a new measure of fit which can be used in the case of quantile–quantile plots. This measure, when applied to Small's and Srivastava's graphical methods provides two new tests for assessing Multivariate Normality. For different sample sizes and numbers of variables, the critical values of these tests were evaluated via simulations. The power of the new tests and its comparison with some other tests for Multivariate Normality are presented herein.
Richie Lee - One of the best experts on this subject based on the ideXlab platform.
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On Rotational Robustness of Shapiro-Wilk Type Tests for Multivariate Normality
Open Journal of Statistics, 2014Co-Authors: Richie Lee, Meng Qian, Yongzhao ShaoAbstract:The Shapiro-Wilk test (SWT) for Normality is well known for its competitive power against numerous one-dimensional alternatives. Several extensions of the SWT to multi-dimensions have also been proposed. This paper investigates the relative strength and rotational robustness of some SWT-based Normality tests. In particular, the Royston’s H-test and the SWT-based test proposed by Villase?or-Alva and Gonzalez-Estrada have R packages available for testing Multivariate Normality; thus they are user friendly but lack of rotational robustness compared to the test proposed by Fattorini. Numerical power comparison is provided for illustration along with some practical guidelines on the choice of these SWT-type tests in practice.
