Heavy-tailed longitudinal data modeling using copulas

By Jiafeng Sun, Edward W. Frees, M. Rosenberg. 2008

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Statistical concepts of a priori and a posteriori risk classification in insurance (2011, methodology): “See, for example, Yip and Yau (2005), Boucher et al.”
Modeling Longitudinal Data Using a Pair-Copula Decomposition of Serial Dependence (2010, unknown): “Meester and MacKay (1994) and Joe (1997, pp. 243–280) provide early examples, while more recent examples include Lambert and Vandenhende (2002), Frees and Wang (2006), Sun, Frees, and Rosenberg (2008), and Domma, Giordano, and Perri (2009).”
Vine Copula Specifications for Stationary Multivariate Markov Chains (2015, background): “…and Wang, 2006), coffee prices (Abegaz and Naik-Nimbalkar, 2008), higher education funding reforms (Dearden et al., 2008), nursing home utilization (Sun et al., 2008), earnings mobility (Bonhomme and Robin, 2009), foreign exchange (Bouyé and Salmon, 2009), stock prices (Domma et al., 2009),…”
Multivariate Frequency-Severity Regression Models in Insurance (2016, background): “However, following this principle would lead to a large number of parameters; this typically yields computational difficulties as well as problems of interpretations, [14].”
Hierarchical Insurance Claims Modeling (2008, background): “Recently, Sun, Frees, and Rosenberg (2008) used the GB2 in a longitudinal data context to forecast nursing home utilization.”