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:: Volume 13, Issue 1 (9-2019) ::
J. of Stat. Sci. 2019, 13(1): 217-233 Back to browse issues page
Simultaneous Test for Independence Among Subvectors of Several Moderately High Dimensional Multivariate Normal Distributions
Dariush Najarzadeh
Abstract:   (1164 Views)

‎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.

Keywords: ‎Multivariate Normal Distribution‎, ‎Likelihood Ratio Test‎, ‎High-Dimensional Data‎, Testing Independence‎, ‎Multivariate Gamma Function.
Full-Text [PDF 289 kb]   (204 Downloads)    
Type of Study: Applied | Subject: Statistical Inference
Received: 2018/01/30 | Accepted: 2018/09/5 | Published: 2019/02/25
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Najarzadeh D. Simultaneous Test for Independence Among Subvectors of Several Moderately High Dimensional Multivariate Normal Distributions. J. of Stat. Sci.. 2019; 13 (1) :217-233
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Volume 13, Issue 1 (9-2019) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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