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October 3, 2025Open Access

Flexible Modeling of Multivariate Skewed and Heavy-Tailed Data via a Non-Central Skew t Distribution: Application to Tumor Shape Data

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Analysis demonstrates superior fit of non-central skew t distribution in tumor shape data, suggesting new modeling approaches.

The non-central skew t distribution effectively models multivariate data with asymmetry and heavy tails.
Simulation studies indicate that maximum likelihood estimation via Monte Carlo is effective for the non-central skew t distribution.
Comparisons show that the non-central skew t model offers better fit than traditional multivariate normal and skew models.
Findings open avenues for advanced likelihood inference and applications in fields requiring complex, non-Gaussian data analysis.

Hasan et al. (2025) studied this question.

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