A new class of bivariate distributions and its mixture
Journal of Multivariate Analysis
Estimating the parameters of the Marshall-Olkin bivariate Weibull distribution by EM algorithm
Computational Statistics & Data Analysis
On the glog-normal distribution and its application to the gene expression problem
Computational Statistics & Data Analysis
Diagnostics for skew-normal nonlinear regression models with AR(1) errors
Computational Statistics & Data Analysis
Divergence measures based on the Shannon entropy
IEEE Transactions on Information Theory
Tailweight, quantiles and kurtosis: A study of competing distributions
Operations Research Letters
On the Marshall-Olkin transformation as a skewing mechanism
Computational Statistics & Data Analysis
Small area estimation using skew normal models
Computational Statistics & Data Analysis
Short communication: On simulating Balakrishnan skew-normal variates
Computational Statistics & Data Analysis
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A new class of distribution functions with not-necessarily symmetric densities, which contains the normal one as a particular case, is introduced. The class thus obtained depends on a set of three parameters, with an additional one to the classical normal distribution being inserted. This new class of skewed distributions is presented as an alternative to the class of skew-normal and Balakrishnan skew-normal distributions, among others. The density and distribution functions of this new class are given by a closed expression which allows us to easily compute probabilities, moments and related measurements. Certain interesting regularity properties reduce the study of this class to one of a subset of standardized distributions. Finally, some applications are shown as examples.