Robust Likelihood Methods Based on the Skew‐t and Related Distributions

By Adelchi Azzalini, Marc G. Genton. 2008

245 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/da451ca3087af92d65d710afa62313459a1dbb11

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In Statistics and Probability

Citations in the corpus

A Heckman Selection-t Model (2012, background): “1989 , Azzalini and Genton 2008 , DiCiccio and Monti 2009 ) also make it an attractive parametric alternative to the normal distribution.”
Multivariate measurement error models based on scale mixtures of the skew–normal distribution (2010, methodology): “Applications of the SSL distribution can be found in Wang and Genton [17].”
Powering Up With Space-Time Wind Forecasting (2010, methodology): “The BST model, like any robust fitting technique, fits to the majority of the data in the fitting window and is insensitive to unusually large or small values ( Azzalini and Genton 2008 ).”
Short‐Term Wind Speed Forecasting for Power System Operations (2012, methodology): “International Statistical Review C© 2012 International Statistical Institute Recently, the bivariate skew-t distribution (Azzalini & Genton, 2008, and references therein) has been used by Hering & Genton (2010) in wind speed forecasting problems, after converting wind speed and wind direction into…”
The centred parametrization for the multivariate skew-normal distribution (2008, methodology): “We would like to thank Antonella Capitanio, Marc Genton and two referees for their comments which have led to improvement of the presentation.”
On Families of Distributions with Shape Parameters (2015, unknown): “The case for interest in such distributions in parametric modelling is, I think, clear (see also Azzalini & Genton, 2008); the purpose of this article is to explore and compare some of the many possible ways of providing them.”
Multivariate log‐skew‐elliptical distributions with applications to precipitation data (2009, methodology): “…the multivariate log-skew-t (or log-t) models, it would be interesting to see if extending these models to allow for component-specific degrees of freedom results in an improved fit, although the construction of such a generalization is difficult, see the discussion in Azzalini and Genton (2008).”
Bayesian Inference and Application of Robust Growth Curve Models Using Student's t Distribution (2013, methodology): “Another possible solution is to use a skew t distribution (Azzalini & Genton, 2008) to accommodate skewness in the data.”
An alternative multivariate skew Laplace distribution: properties and estimation (2010, methodology): “ Azzalini and Genton (2008) consider the wind speed dataset, which consists of hourly average wind speed collected at three different locations.”
LIKELIHOOD BASED INFERENCE FOR SKEW-NORMAL INDEPENDENT LINEAR MIXED MODELS (2010, background): “(2007) and Azzalini and Genton (2007). Moreover, for this model we have in Proposition 1 that Y0 ∼ tp(μ,Σ, ν), i.”
Short-term density forecasting of wave energy using ARMA-GARCH models and kernel density estimation (2016, methodology): “Among various forms of multivariate skewed t distributions, we used the definition by Azzalini and Genton (2008). In our empirical study,”
Bayesian inference for shape mixtures of skewed distributions, with application to regression analysis (2008, methodology): “…in the form introduced by Azzalini and Capitanio (2003) with pdf 2t(z; ν)T ( √ ν + 1α1z/ √ ν + z2; ν+1), where t(z; ν) and T (z; ν) are the Student-t pdf and cdf, respectively, is obtained with S2 ∼ Gamma(ν/2, ν/2) and S1 ≡ 1; see also Azzalini and Genton (2008) for additional properties.”
Robust linear mixed models with skew-normal independent distributions from a Bayesian perspective (2009, unknown): “Applications of the ST distribution to robust estimation can be found in Lin et al. (2007) and Azzalini and Genton (2008) .”
Skew-symmetric distributions and Fisher information -- a tale of two densities (2012, background): “Azzalini and Genton [9] therefore once again emphasize the need for a clarification of the Fisher singularity phenomenon in order to “remove, or at least alleviate, the necessity of an alternative parametrization.”