4 citations · 7 across the 4 of their papers we have counts for
5 papers
Dynamic estimation with random forests for discrete-time survival data
Hoora Moradian, Weichi Yao, Denis Larocque +2
Time-varying covariates are often available in survival studies and estimation of the hazard function needs to be updated as new information becomes available. In this paper, we in…
Statistical inference for a mixture of Markov jump processes
Halina Frydman, Budhi Surya
We estimate a general mixture of Markov jump processes. The key novel feature of the proposed mixture is that the transition intensity matrices of the Markov processes comprising t…
Ensemble methods for survival function estimation with time-varying covariates
Weichi Yao, Halina Frydman, Denis Larocque +1
Survival data with time-varying covariates are common in practice. If relevant, they can improve on the estimation of survival function. However, the traditional survival forests -…
The Mixture of Markov Jump Processes: Monte Carlo Method and the EM Estimation
H. Frydman, B. A. Surya
This paper discusses tractable development and statistical estimation of a continuous time stochastic process with a finite state space having non-Markov property. The process is f…
An Ensemble Method for Interval-Censored Time-to-Event Data
Weichi Yao, Halina Frydman, Jeffrey S. Simonoff
Interval-censored data analysis is important in biomedical statistics for any type of time-to-event response where the time of response is not known exactly, but rather only known…