Gómez, Héctor W.Héctor W.GómezTorres, Francisco J.Francisco J.TorresBolfarine, HelenoHelenoBolfarine2026-10-192026-10-192007-01-24Gómez, Héctor W.; Torres, Francisco J.; Bolfarine, Heleno (2007-01-24). Large-sample inference for the Epsilon-Skew-t distribution. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 36 (1-4), 73-81. https://doi.org/10.1080/036109206009665140361-09261532-415Xhttps://hdl.handle.net/20.500.12740/25335The main object of this article is to discuss maximum likelihood inference for the epsilon-skew-t distribution. Special cases of this distribution include the epsilon-skew-Cauchy and the epsilon-skew-normal distributions. We derive the information matrix for the maximum likelihood estimators. The approach is applied to a data set presenting significant amount of skewness and heavy tails. In the application we consider the epsilon-skew-t distribution with known and unknown degrees of freedom parameter, showing great flexibility in adjusting to skew data with heavy tails.eninformation matrixkurtosismaximum likelihoodskewnessArticulohttps://doi.org/10.1080/03610920600966514