Article ID Journal Published Year Pages File Type
1153144 Statistics & Probability Letters 2010 9 Pages PDF
Abstract

We prove uniform consistency of Random Survival Forests (RSF), a newly introduced forest ensemble learner for analysis of right-censored survival data. Consistency is proven under general splitting rules, bootstrapping, and random selection of variables—that is, under true implementation of the methodology. Under this setting we show that the forest ensemble survival function converges uniformly to the true population survival function. To prove this result we make one key assumption regarding the feature space: we assume that all variables are factors. Doing so ensures that the feature space has finite cardinality and enables us to exploit counting process theory and the uniform consistency of the Kaplan–Meier survival function.

Related Topics
Physical Sciences and Engineering Mathematics Statistics and Probability
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