Skewed distributions generated by the normal kernel

By Saralees Nadarajah, Samuel Kotz. 2003

131 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/cf11a818c47012b3a4cb6a8f70dd62c7f2f76ed2

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In Statistics and Probability

Citations in the corpus

Bayesian inference for shape mixtures of skewed distributions, with application to regression analysis (2008, methodology): “These distributions were studied by Nadarajah and Kotz (2003) and Gómez, Venegas and Bolfarine (2007), and can be obtained from (5) with S1 ∼ Gamma(ν/2, ν/2) and S2 ≡ 1, and S2 = S1 ∼ Gamma(ν/2, ν/2), respectively.”
The Skew‐normal Distribution and Related Multivariate Families * (2005, background): “The paper of Nadarajah & Kotz (2003) has a similar target in the case when f0 is kept equal to / and G varies.”
A nonparametric method for estimating asymmetric densities based on skewed Birnbaum–Saunders distributions applied to environmental data (2013, methodology): “(iii) The least squares cross validation (LSCV) method may be used to select the bandwidth h, which chooses it by minimizing the cross validation criterion defined as LSCVðhÞ 1⁄4 R1 0 bf 2 h ðxÞdx ð2=nÞ Pn i1⁄41 bfh; iðxiÞ; where bfh is a nonnegative asymmetric kernel density estimate of bandwidth h”
Generalized skew-Cauchy distribution ☆ (2007, background): “Nadarajah and Kotz (2003) considered the models that f is taken to be a normal p.d.f. with zero mean, while G is taken to come from one of the above continuous symmetric distributions.”
Bimodal extension based on the skew‐normal distribution with application to pollen data (2011, background): “The general result in Rotnitzky et al. (2000) concerning the maximum likelihood estimator for the parameter vector θ = (θ1, . . . , θ) can be applied in this context to establish consistency and asymptotic normality for the MLEs. Rotnitzky et al. (2000) derive the asymptotic distribution for the MLE”