A Hidden Markov Approach to Disability Insurance

DOI10.1080/10920277.2017.1387570zbMath1393.62044arXiv1412.7334OpenAlexW2216649368MaRDI QIDQ4567964

Björn Löfdahl, Boualem Djehiche

Publication date: 20 June 2018

Published in: North American Actuarial Journal (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1412.7334

zbMATH Keywords

disability insuranceexpectation-maximization algorithmhidden Markov approach

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Markov processes: estimation; hidden Markov models (62M05)

Related Items (1)

Exact long time behavior of some regime switching stochastic processes

Cites Work

• Unnamed Item
• Modeling and Forecasting U.S. Mortality
• Bayesian Poisson log-bilinear mortality projections
• Robust forecasting of mortality and fertility rates: a functional data approach
• On the convergence properties of the EM algorithm
• Estimating the dimension of a model
• A Poisson log-bilinear regression approach to the construction of projected lifetables.
• The Solvency II square-root formula for systematic biometric risk
• Risk aggregation and stochastic claims reserving in disability insurance
• Log-concave measures
• Regression and time series model selection in small samples
• Stochastic modelling of disability insurance in a multi-period framework
• Modelling the recent time trends in UK permanent health insurance recovery, mortality and claim inception transition intensities

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