Composite Lognormal–Pareto model with random threshold

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Nonlife Ratemaking and Risk Management with Bayesian Additive Models for Location, Scale and Shape (2013, background): “Let us nevertheless mention the composite models considered, e.g., in Pigeon and Denuit (2011) which can accomodate a mix of small and large claims but for which no regression analysis is available, yet.”
Modeling loss data using mixtures of distributions (2016, methodology): “Further extensions in this stream of research on composite models were proposed by Pigeon and Denuit (2011), who introduced the threshold value as a random variable in existing Log-normalPareto composite models, Nadarajah and Bakar (2014), who suggested a composite Log-normal-Burr model, and…”
Individual Loss Reserving with the Multivariate Skew Normal Model (2011, unknown): “The modeling of the first payment could be refined and adjusted to large losses, using the Lognormal-Pareto distribution (see Pigeon & Denuit (2011)).”
FITTING MIXTURES OF ERLANGS TO CENSORED AND TRUNCATED DATA USING THE EM ALGORITHM (2015, methodology): “We detected some limitations of mixtures of Erlangs in approximating heavy-tailed distributions and suggest combining our methodology with the extreme value methodology using a body-tail approach (Lee et al., 2012; Pigeon and Denuit, 2011).”