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简介

Camilo's research focuses on the development of a general unified statistical framework for estimating and testing linear and non-linear latent variable models. In particular, he extends the Generalised Additive Models for Location, Shape and Scale (GAMLSS) framework (Rigby and Stasinopoulos, 2005) to models with latent variables (Bartholomew et. al., 2011). The proposed framework allows for more flexible functional forms on the measurement equations not only for the mean, but also for higher order moments. The estimation is done through a novel and computationally efficient penalised method. Moreover, Camilo is also interested in applied statistical modelling, computational statistics, and causal inference.

数据校验于 9/6/2026数据来源

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