Actuarial Data Science
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Regression Modeling with Actuarial and Financial Applications
Author: Edward W. Frees
language: en
Publisher: Cambridge University Press
Release Date: 2010
This book teaches multiple regression and time series and how to use these to analyze real data in risk management and finance.
Solutions Manual for Actuarial Mathematics for Life Contingent Risks
Author: David C. M. Dickson
language: en
Publisher: Cambridge University Press
Release Date: 2012-03-26
"This manual presents solutions to all exercises from Actuarial Mathematics for Life Contingent Risks (AMLCR) by David C.M. Dickson, Mary R. Hardy, Howard Waters; Cambridge University Press, 2009. ISBN 9780521118255"--Pref.
Effective Statistical Learning Methods for Actuaries II
This book summarizes the state of the art in tree-based methods for insurance: regression trees, random forests and boosting methods. It also exhibits the tools which make it possible to assess the predictive performance of tree-based models. Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and numerical illustrations or case studies. All numerical illustrations are performed with the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. In particular, master's students in actuarial sciences and actuaries wishing to update their skills in machine learning will find the book useful. This is the second of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance.