Bivariate distribution regression with application to insurance data
From MaRDI portal
Publication:6152694
DOI10.1016/j.insmatheco.2023.08.005arXiv2203.12228MaRDI QIDQ6152694
Dan Zhu, Tatsushi Oka, Yunyun Wang
Publication date: 13 February 2024
Published in: Insurance Mathematics \& Economics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2203.12228
Applications of statistics to actuarial sciences and financial mathematics (62P05) Actuarial mathematics (91G05)
Cites Work
- Unnamed Item
- Asymptotics for argmin processes: convexity arguments
- Exchangeably weighted bootstraps of the general empirical process
- Weak convergence and empirical processes. With applications to statistics
- Insurance risk analysis of financial networks vulnerable to a shock
- Generalized linear models for dependent frequency and severity of insurance claims
- A mixed copula model for insurance claims and claim sizes
- Improving point and interval estimators of monotone functions by rearrangement
- Response models for mixed binary and quantitative variables
- A Correlated Probit Model for Joint Modeling of Clustered Binary and Continuous Responses
- Asymptotic Statistics
- Methods for Estimating a Conditional Distribution Function
- Pair Copula Constructions for Insurance Experience Rating
- Misspecification Testing in a Class of Conditional Distributional Models
- Nonparametric Estimation of Copula Regression Models With Discrete Outcomes
- Optimization with Multivariate Conditional Value-at-Risk Constraints
- Inference on Counterfactual Distributions
- Multivariate Correlation Models with Mixed Discrete and Continuous Variables
- Multivariate conditional transformation models
- Maximum Likelihood Estimation of Misspecified Models
This page was built for publication: Bivariate distribution regression with application to insurance data