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Interval censored recursive forests
- Source :
- J Comput Graph Stat
- Publication Year :
- 2021
- Publisher :
- Taylor and Francis, 2021.
-
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.
- Subjects :
- Statistics and Probability
FOS: Computer and information sciences
Statistics::Theory
Statistics::Other Statistics
02 engineering and technology
01 natural sciences
Article
Methodology (stat.ME)
010104 statistics & probability
Survival data
Statistics
0202 electrical engineering, electronic engineering, information engineering
Discrete Mathematics and Combinatorics
Statistics::Methodology
0101 mathematics
Survival analysis
Statistics - Methodology
Mathematics
Statistics::Applications
Estimator
Statistics::Computation
Nonparametric regression
Random forest
Tree (data structure)
Kernel smoother
Interval (graph theory)
020201 artificial intelligence & image processing
Statistics, Probability and Uncertainty
Subjects
Details
- Language :
- English
- ISSN :
- 10618600
- Database :
- OpenAIRE
- Journal :
- J Comput Graph Stat
- Accession number :
- edsair.doi.dedup.....feac90caa1a73480ae0f89d4493f29ed