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Bayesian Claims Reserving Methods in Non-life Insurance with Stan: An Introduction

Autor Guangyuan Gao
en Limba Engleză Hardback – 17 ian 2019
This book first provides a review of various aspects of Bayesian statistics. It then investigates three types of claims reserving models in the Bayesian framework: chain ladder models, basis expansion models involving a tail factor, and multivariate copula models. For the Bayesian inferential methods, this book largely relies on Stan, a specialized software environment which applies Hamiltonian Monte Carlo method and variational Bayes.  
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Specificații

ISBN-13: 9789811336089
ISBN-10: 9811336083
Pagini: 193
Ilustrații: XII, 205 p. 72 illus., 62 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.49 kg
Ediția:1st ed. 2018
Editura: Springer Nature Singapore
Colecția Springer
Locul publicării:Singapore, Singapore

Cuprins

Chapter1 Introduction.- Chapter2 Bayesian Fundamentals.- Chapter3 Advanced Bayesian Computation.- Chapter4 Bayesian Chain Ladder Models.- Chapter5 Bayesian Basis Expansion Models.- Chapter6 Multivariate Modelling Using Copulas.- Chapter7 Epilogue.

Notă biografică

Guangyuan Gao, lecturer in actuarial science, School of Statistics at the Renmin University of China.


Textul de pe ultima copertă

This book first provides a review of various aspects of Bayesian statistics. It then investigates three types of claims reserving models in the Bayesian framework: chain ladder models, basis expansion models involving a tail factor, and multivariate copula models. For the Bayesian inferential methods, this book largely relies on Stan, a specialized software environment which applies Hamiltonian Monte Carlo method and variational Bayes.  

Caracteristici

The first book provides explicit Stan code for non-life claims reserving The book has a thorough review of many aspects of Bayesian statistics, and relates them to claims reserving problem The book addresses three important points in claims reserving: proposing a stochastic payments per claim incurred model (Section 4), estimating the tail factor via basis expansion models (Section 5), and aggregating claims liabilities by copulas (Section 6)