Estimating loss reserves using hierarchical Bayesian Gaussian process regression with input warping
type: Item
instance of: scholarly article
title: Estimating loss reserves using hierarchical Bayesian Gaussian process regression with input warping
zbMATH Open document ID: 1403.62192
author: Nathan Lally
author: Brian M. Hartman
published in: Insurance Mathematics \& Economics
publication date: 2018-10-19T00:00:00Z
Mathematics Subject Classification ID: 62P05
Mathematics Subject Classification ID: 62M30
Mathematics Subject Classification ID: 91B30
zbMATH DE Number: 6958595
zbMATH Keywords: loss reserves
zbMATH Keywords: claims triangles
zbMATH Keywords: input warping
zbMATH Keywords: Gaussian process regression
zbMATH Keywords: spatial statistics
describes a project that uses: NUTS
describes a project that uses: Stan
MaRDI profile type: Publication
full work available at URL: j.insmatheco.2018.06.008
OpenAlex ID: W2883706670
cites work: The Geometry of Random Fields
cites work: Claims reserving: A correlated Bayesian model
cites work: Q3058567
cites work: The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
cites work: A NON-PARAMETRIC METHOD FOR INCURRED BUT NOT REPORTED CLAIM RESERVE ESTIMATION
cites work: Model Uncertainty in Claims Reserving within Tweedie's Compound Poisson Models
cites work: A Bayesian Log-Normal Model for Multivariate Loss Reserving
cites work: Interpolation of spatial data. Some theory for kriging
cites work: Q3394879
cites work: Stochastic claims reserving methods in insurance
Wikidata QID: Q129473706
DOI: 10.1016/J.INSMATHECO.2018.06.008
description: scientific article; zbMATH DE number 6958595