Stochastic loss reserving with mixture density neural networks-Reference-Cited by-同舟云学术

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Stochastic loss reserving with mixture density neural networks

Published:2022-07 Issue: Volume:105 Page:144-174
ISSN:0167-6687
Container-title:Insurance: Mathematics and Economics
language:en
Short-container-title:Insurance: Mathematics and Economics

Author:

Al-Mudafer Muhammed Taher^ORCID,Avanzi Benjamin^ORCID,Taylor Greg,Wong Bernard

Funder

Australian Research Council

Publisher

Elsevier BV

Subject

Statistics, Probability and Uncertainty,Economics and Econometrics,Statistics and Probability

Reference41 articles.

1. Synthetic: an individual insurance claim simulator with feature control;Avanzi;Insurance. Mathematics & Economics,2021

2. The actuary and ibnr techniques: a machine learning approach;Balona,2020

3. On the use of cross-validation for time series predictor evaluation;Bergmeir;Information Sciences,2012

4. Mixture Density Networks;Bishop,1994

5. Pattern Recognition and Machine Learning (Information Science and Statistics);Bishop,2006

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1. Ensemble distributional forecasting for insurance loss reserving;Scandinavian Actuarial Journal;2024-07-03

2. Machine Learning with High-Cardinality Categorical Features in Actuarial Applications;ASTIN Bulletin;2024-04-11

3. Machine learning in long-term mortality forecasting;The Geneva Papers on Risk and Insurance - Issues and Practice;2024-04

4. GEMAct: a Python package for non-life (re)insurance modeling;Annals of Actuarial Science;2024-02-14

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