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Cites:

Information Journal Paper

Title

Simultaneous Test for Independence Among Subvectors of Several Moderately High Dimensional Multivariate Normal Distributions

Pages

  217-233

Abstract

 Testing the Hypothesis of independence of a p-variate vector subvectors, as a pretest for many others related tests, is always as a matter of interest. When the sample size n is much larger than the dimension p, the Likelihood Ratio Test (LRT) with chisquare approximation, has an acceptable performance. However, for moderately High-Dimensional Data by which n is not much larger than p, the chisquare approximation for null distribution of the LRT statistic is no more usable. As a general case, here, a simultaneous subvectors independence testing procedure in all k p-variate normal distributions is considered. To test this hypothesis, a normal approximation for the null distribution of the LRT statistic was proposed. A simulation study was performed to show that the proposed normal approximation outperforms the chisquare approximation. Finally, the proposed testing procedure was applied on prostate cancer data.

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    APA: Copy

    Najarzadeh, Dariush. (2019). Simultaneous Test for Independence Among Subvectors of Several Moderately High Dimensional Multivariate Normal Distributions. JOURNAL OF STATISTICAL SCIENCES, 13(1 ), 217-233. SID. https://sid.ir/paper/124119/en

    Vancouver: Copy

    Najarzadeh Dariush. Simultaneous Test for Independence Among Subvectors of Several Moderately High Dimensional Multivariate Normal Distributions. JOURNAL OF STATISTICAL SCIENCES[Internet]. 2019;13(1 ):217-233. Available from: https://sid.ir/paper/124119/en

    IEEE: Copy

    Dariush Najarzadeh, “Simultaneous Test for Independence Among Subvectors of Several Moderately High Dimensional Multivariate Normal Distributions,” JOURNAL OF STATISTICAL SCIENCES, vol. 13, no. 1 , pp. 217–233, 2019, [Online]. Available: https://sid.ir/paper/124119/en

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