An Individual Claims History Simulation Machine
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[1] Paul J. Werbos,et al. Applications of advances in nonlinear sensitivity analysis , 1982 .
[2] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[3] George Cybenko,et al. Approximation by superpositions of a sigmoidal function , 1989, Math. Control. Signals Syst..
[4] Kurt Hornik,et al. Multilayer feedforward networks are universal approximators , 1989, Neural Networks.
[5] T. Mack. Distribution-free Calculation of the Standard Error of Chain Ladder Reserve Estimates , 1993, ASTIN Bulletin.
[6] Ronald,et al. Learning representations by backpropagating errors , 2004 .
[7] G. McGuire,et al. Individual Claim Loss Reserving Conditioned by Case Estimates , 2008, Annals of Actuarial Science.
[8] G. Samorodnitsky,et al. Prediction of outstanding payments in a Poisson cluster model , 2011 .
[9] Katrien Antonio,et al. Micro-level stochastic loss reserving for general insurance , 2012 .
[10] M. Denuit,et al. INDIVIDUAL LOSS RESERVING WITH THE MULTIVARIATE SKEW NORMAL FRAMEWORK , 2013, ASTIN Bulletin: The Journal of the International Actuarial Association.
[11] Jens Perch Nielsen,et al. The Link Between Classical Reserving and Granular Reserving Through Double Chain Ladder and its Extensions , 2016 .
[12] Mario V. Wüthrich. Machine learning in individual claims reserving , 2016 .
[13] M. Wüthrich,et al. Understanding Reporting Delay in General Insurance , 2016 .
[14] Mario V. Wüthrich,et al. Neural networks applied to chain–ladder reserving , 2018, European Actuarial Journal.