| Literature DB >> 35685204 |
Hunyong Cho1, Nicholas P Jewell2, Michael R Kosorok3.
Abstract
We propose interval censored recursive forests (ICRF), an iterative tree ensemble method for interval censored survival data. This nonparametric regression estimator addresses the splitting bias problem of existing tree-based methods and iteratively updates survival estimates in a self-consistent manner. Consistent splitting rules are developed for interval censored data, convergence is monitored using out-of-bag samples, and kernel-smoothing is applied. The ICRF is uniformly consistent and displays high prediction accuracy in both simulations and applications to avalanche and national mortality data. An R package icrf is available on CRAN and Supplementary Materials for this article are available online.Entities:
Keywords: interval censored data; kernel-smoothing; quasi-honesty; random forest; self-consistency; survival analysis
Year: 2021 PMID: 35685204 PMCID: PMC9173656 DOI: 10.1080/10618600.2021.1987253
Source DB: PubMed Journal: J Comput Graph Stat ISSN: 1061-8600 Impact factor: 1.884