Kalman Filter Learning Algorithms and State Space Representations for Stochastic Claims Reserving
Kalman Filter Learning Algorithms and State Space Representations for Stochastic Claims Reserving
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Basel: MDPI AG
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English
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Basel: MDPI AG
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In stochastic claims reserving, state space models have been used for almost 40 years to forecast loss reserves and to compute their mean squared error of prediction. Although state space models and the associated Kalman filter learning algorithms are very powerful and flexible tools, comparatively few articles on this topic were published during t...
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Kalman Filter Learning Algorithms and State Space Representations for Stochastic Claims Reserving
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TN_cdi_doaj_primary_oai_doaj_org_article_557eec4ca5fa483a94c6f9fe7170ea8b
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_557eec4ca5fa483a94c6f9fe7170ea8b
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ISSN
2227-9091
E-ISSN
2227-9091
DOI
10.3390/risks9060112
