Results 221 to 230 of about 30,095 (256)
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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 ...
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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 ...
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Skewed distributions generated by the normal kernel
Statistics & Probability Letters, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nadarajah, Saralees, Kotz, Samuel
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Sampling distributions of skew normal populations associated with closed skew normal distributions
Random Operators and Stochastic Equations, 2019Abstract The sample mean and sample variance are commonly used statistics in our study. In this paper, distributions of the sample mean and sample variance from a skew normal population are derived under closed skew normal (CSN) settings.
Zhu, Xiaonan +3 more
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Geometric Skew Normal Distribution
Sankhya B, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A Bayesian interpretation of the multivariate skew-normal distribution
Statistics & Probability Letters, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
LISEO, Brunero, LOPERFIDO N.
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A doubly skewed normal distribution
Statistics, 2014We consider a distribution obtained by combining two well-known mechanisms for generating skewed distributions. In this manner we arrive at a flexible model which subsumes and extends several skew distributions which have been discussed in the literature.
Barry C. Arnold +2 more
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On bias reduction estimators of skew-normal and skew-t distributions
Journal of Applied Statistics, 2020A particular concerns of researchers in statistical inference is bias in parameters estimation. Maximum likelihood estimators are often biased and for small sample size, the first order bias of them can be large and so it may influence the efficiency of the estimator. There are different methods for reduction of this bias.
Mohammad Mahdi, Maghami +2 more
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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
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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
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Skewness and mixtures of normal distributions
Communications in Statistics - Theory and Methods, 1988The effect of skewness on hypothesis tests for the existence of a mixture of univariate and bivariate normal distributions is examined through a Monte Carlo study. A likelihood ratio test based on results of the simultaneous estimation of skewness parameters, derived from power transformations, with mixture parameters is proposed.
Nicholas J. Schork, M. Anthony Schork
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