Hierarchical Gaussian Process Models For Loss Reserving
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...
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my-usm-ep.591382023-08-18T01:19:56Z Hierarchical Gaussian Process Models For Loss Reserving 2021-12 Ang, Zi Qing QA1 Mathematics (General) 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. 2021-12 Thesis http://eprints.usm.my/59138/ http://eprints.usm.my/59138/1/24%20Pages%20from%20ANG%20ZI%20QING%20-%20TESIS.pdf application/pdf en public masters Perpustakaan Hamzah Sendut Pusat Pengajian Sains Matematik |
| institution |
Universiti Sains Malaysia |
| collection |
USM Institutional Repository |
| language |
English |
| topic |
QA1 Mathematics (General) |
| spellingShingle |
QA1 Mathematics (General) Ang, Zi Qing Hierarchical Gaussian Process Models For Loss Reserving |
| description |
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. |
| format |
Thesis |
| qualification_level |
Master's degree |
| author |
Ang, Zi Qing |
| author_facet |
Ang, Zi Qing |
| author_sort |
Ang, Zi Qing |
| title |
Hierarchical Gaussian Process Models For Loss Reserving |
| title_short |
Hierarchical Gaussian Process Models For Loss Reserving |
| title_full |
Hierarchical Gaussian Process Models For Loss Reserving |
| title_fullStr |
Hierarchical Gaussian Process Models For Loss Reserving |
| title_full_unstemmed |
Hierarchical Gaussian Process Models For Loss Reserving |
| title_sort |
hierarchical gaussian process models for loss reserving |
| granting_institution |
Perpustakaan Hamzah Sendut |
| granting_department |
Pusat Pengajian Sains Matematik |
| publishDate |
2021 |
| url |
http://eprints.usm.my/59138/1/24%20Pages%20from%20ANG%20ZI%20QING%20-%20TESIS.pdf |
| _version_ |
1776101254126108672 |