Weibull Racing Time-to-event Modeling and Analysis of Online Borrowers' Loan Payoff and Default
Year: 2019
Type: preprint
Abstract: We propose Weibull delegate racing (WDR) to explicitly model surviving under competing events and to interpret how the covariates accelerate or decelerate the event time. It explains non-monotonic covariate effects by racing a potentially infinite number of sub-events, and consequently relaxes the ubiquitous proportional-hazards assumption which may be too restrictive. For inference, we develop a Gibbs-sampler-based MCMC algorithm along with maximum a posteriori estimations for big data applications. We analyze time to loan payoff and default on this http URL, demonstrating not only a distinguished performance of WDR, but also the value of standard and soft information.
Source: arXiv (Cornell University)
Authors: Quan Zhang, Qiang Gao, Mingfeng Lin, Mingyuan Zhou
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2985558719