The Kumaraswamy Generalized Half-Normal Distribution for Skewed Positive Data

By Gauss Moutinho Cordeiro, Rodrigo Rossetto Pescim, Edwin M. M. Ortega. Journal of Data Science, 2012

75 citations recorded by the source corpus.

For the first time, we propose and study the Kumaraswamy generalized half-normal distribution for modeling skewed positive data. The half-normal and generalized half-normal (Cooray and Ananda, 2008) distributions are special cases of the new model. Various of its structural properties are derived, including explicit expressions for the density function, moments, generating and quantile functions, mean deviations and moments of the order statistics. We investigate maximum likelihood estimation of the parameters and derive the expected information matrix. The proposed model is modified to open the possibility that long-term survivors may be presented in the data. Its applicability is illustrated by means of four real data sets.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/57ba78ac69a7490c249e8cb42b7b522fe576a231

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Citations in the corpus

The Burr XII System of densities: properties, regression model and applications (2018, methodology): “[28] analysed these data using the Kumaraswamy generalized half-normal (Kw-GHN) distribution and prove empirically that this distribution can provide better fits than the generalized half-normal (GHN) and half-normal (HN) models [29].”
The Transmuted Topp-Leone G Family of Distributions: Theory, Characterizations and Applications (2021, background): “Note that a set of functions satisfying the di¤erential equation (16) is given in Proposition 4.”
A new method for generating families of continuous distributions (2013, unknown): “[8].”