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Arrué, J., Arellano-Valle, R.B., Calderín-Ojeda, E., Venegas, O. and Gómez, H.W. (2023) Likelihood Based Inference and Bias Reduction in the Modified Skew-t-Normal Distribution. Mathematics, 11, Article 3287.
https://doi.org/10.3390/math11153287

has been cited by the following article:

• TITLE: Higher-Order Expansions of Sample Range from the Skew-t-Normal Distribution

  AUTHORS: Wanrou Yang

  KEYWORDS: Higher-Order Expansion, Skew-t-Normal Distribution, Rate of Convergence, Sample Range

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.13 No.11, November 20, 2025

  ABSTRACT: For an independent and identically distributed skew-t-normal random sequence, this paper establishes the limit distribution of normalized sample range M n − m n . Based on the optimal normalized constants, the higher-order asymptotic expansion of the distribution function of sample range M n − m n is further derived, and its convergence rate is given. In addition, the approximate accuracy between the empirical value and the asymptotic theoretical value is systematically compared by numerical simulation.