Hierarchical Gaussian Process Models For Loss Reserving

Publication:
Hierarchical Gaussian Process Models For Loss Reserving

dc.contributor.author	Ang,Zi Qing
dc.date.accessioned	2023-08-16T02:36:14Z
dc.date.available	2023-08-16T02:36:14Z
dc.date.issued	2021-12
dc.description.abstract	Loss reserving is one of the main activities of actuaries in the insurance industry and is done to ensure the financial health of companies as well as protecting consumers’ interest. Techniques applied by the practitioners are highly regulated, but researchers are still ongoing in the pursuit of finding methods to improve predictive accuracy and to establish a measure of predictive uncertainties. Diverting from the link ratio methods, researchers have experimented with parametric models such as growth-curve models and models involving dynamical systems, as well as nonparametric models. Researchers in this field have increasingly shown interests in utilizing Bayesian methods to measure predictive uncertainties.
dc.identifier.uri	https://erepo.usm.my/handle/123456789/17273
dc.subject	Hierarchical Gaussian
dc.subject	Process Models For Loss Reserving
dc.title	Hierarchical Gaussian Process Models For Loss Reserving
dc.type	Resource Types::text::thesis::master thesis
dspace.entity.type	Publication
oairecerif.author.affiliation	Universiti Sains Malaysia

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