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Variance-calibrated cross-individual bootstrapping for small-sample neuroscience. [PDF]
Sci RepUyanik I.
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Bayesian Discrepancy Measure: Higher-Order and Skewed Approximations. [PDF]
Entropy (Basel)Bortolato E +3 more
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, 2004 The book reviews the state-of-the-art advances in skew-elliptical distributions and provides many new developments in a single volume, collecting theoretical results and applications previously scattered throughout the literature. The main goal of this research area is to develop flexible parametric classes of distributions beyond the classical normal ...
DALLA VALLE, ALESSANDRA
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Geometric Skew Normal Distribution
Sankhya B, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
D. Kundu
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, 2017 AbstractThis chapter considers the univariate skew-normal distribution, a generalization of the normal that includes the normal as a special case. The most natural parametrization is non-standard. This is because the Fisher information matrix is then singular at the true parameter value when the true model is the normal special case. The log-likelihood
Russell Cheng
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A multivariate modified skew-normal distribution
Statistical Papers, 2023 We introduce a multivariate version of the modified skew-normal distribution, which contains the multivariate normal distribution as a special case. Unlike the Azzalini multivariate skew-normal distribution, this new distribution has a nonsingular Fisher
Sagnik Mondal +2 more
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Characterization of the skew-normal distribution
Annals of the Institute of Statistical Mathematics, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gupta, Arjun K. +2 more
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, 2011 An introductory account of the skew-normal ...
Adelchi Azzalini, AZZALINI, ADELCHI
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