A skew extension of the t‐distribution, with applications

By M. Chris Jones, Malcolm J. Faddy. 2003

367 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/ad384555c46a7aefa4c4ee7ff5c7701fd5ec2dba

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In Statistics and Probability

Citations in the corpus

Asymmetry and Gradient Asymmetry Functions: Density‐Based Skewness and Kurtosis (2008, methodology): “The glass fibre data have recently been used to illustrate the fitting of various skew t distributions (Jones & Faddy, 2003; Ferreira & Steel, 2006).”
Generalized beta-generated distributions (2012, methodology): “Two important special cases are the classical beta distribution (a = 1), and the Kumaraswamy distribution (p = 1). The distribution of Kumaraswamy (1980) is commonly termed the ‘minimax’ distribution.”
Finite mixture modelling using the skew normal distribution (2007, methodology): “Introduction Finite mixture models have been broadly developed and widely applied to classification, clustering, density estimation and pattern recognition problems, as shown by Titterington, Smith and Markov (1985), McLachlan and Basord (1988), McLachlan and Peel (2000), and the references therein.”
The Generalized Hyperbolic Skew Student’s t-Distribution (2006, methodology): “For the NIG distribution, we used the EM-algorithm described in Karlis (2002), with the moment estimates as initial values.”
Using the Box-Cox t distribution in GAMLSS to model skewness and kurtosis (2006, methodology): “Models 7–10 and 13 have distributions allowing the modelling of both skewness and kurtosis: Johnson’s Su (JSU) (Johnson, 1949), ST (Jones and Faddy, 2003), skew exponential power (SEP) (Azzalini, 1986; DiCiccio and Monti, 2004), BCT and Box–Cox power exponential (BCPE) (Rigby and Stasinopoulos,…”
A New Class of Multivariate Skew Densities, with Application to GARCH Models (2002, background): “is not obvious that the thicker tail should be necessarily the long one. Jones and Faddy (2000) ”
Joint modelling of location and scale parameters of the t distribution (2004, methodology): “Lange et al. (1989), Liu and Rubin (1994, 1995) and Pinheiro et al.”
Modelling skewness dynamics in series of financial data using skewed location-scale distributions (2001, neutral): “"$ & "# & "$ 6 "# 6 "$ Pr(Return >= x | skewed stable) / Pr(Return >= x | skewed Student) D”