Bias prevention of maximum likelihood estimates for scalar skew normal and skew t distributions

By Nicola Sartori. 2006

124 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/c03f16c557d001b1a3ee21b3918741380498d6bd

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In Global and Planetary Change

In Statistics and Probability

Citations in the corpus

Median bias reduction of maximum likelihood estimates (2016, unknown): “The modified score (4) (see Sartori, 2006) is U∗(θ) = U(θ)− θa42(θ)/{2a22(θ)}.”
Maximum penalized likelihood estimation for skew-normal and skew-t distributions (2012, methodology): “The cases where α̂ diverged have been excluded from the computation of these summaries, in agreement with Sartori (2006) and Bayes & Branco (2007).”
Modeling jointly low, moderate, and heavy rainfall intensities without a threshold selection (2016, background): “Skewness parameters like δ or κ2 are difficult to estimate by ML, as it was noticed 356 by Sartori [2006] for the skew normal case and Ribereau et al. [2014] for the extended 357 GEV case.”
Multivariate log‐skew‐elliptical distributions with applications to precipitation data (2009, methodology): “2003; Sartori 2006; Pewsey 2000, 2006; Azzalini and Genton 2008; Arellano-Valle and Azzalini”
Analyzing skewed data by power normal model (2008, background): “Solutions to this problem have been proposed by Monti (2003), Liseo and Loperfido (2006) and Sartori (2006) .”
Generalized beta-generated distributions (2012, methodology): “These data were previously considered in Section 6.3 of Azzalini and Capitanio (1999) and in Sartori (2006), also available at http://azzalini.stat.unipd.it/SN/index.html.”
A unified view on skewed distributions arising from selections (2006, background): “It is currently the subject of vigorous research efforts and recent advances on this topic include work by Azzalini (2005), Azzalini & Capitanio (1999, 2003), DiCiccio & Monti (2004), Ma, Genton & Tsiatis (2005), Ma & Hart (2006), Pewsey (2000, 2006), and Sartori (2006).”
Bias reduction in exponential family nonlinear models (2009, unknown): “The modified-score functions approach to bias reduction (Firth, 1993) is continually gaining in popularity (e.g. Mehrabi & Matthews, 1995; Pettitt et al., 1998; Heinze & Schemper, 2002; Bull et al., 2002; Zorn, 2005; Sartori, 2006; Bull et al., 2007), because of the superior properties of the bias-r”