Nonparametric Estimation for Nonhomogeneous Markov Processes in the Problem of Competing Risks

Nonparametric Estimation for Current Status Data with Competing Risks

Nonparametric Estimation of Nonhomogeneous Poisson Processes Using Wavelets

Nonhomogeneous Poisson processes (NHPPs) are frequently used in stochastic simulations to model nonstationary point processes. These NHPP models are often constructed by estimating the rate function from one or more observed realizations of the process. Both parametric and nonparametric models have been developed for the NHPP rate function. The current parametric models require prior knowledge ...

Parametric Estimation in a Recurrent Competing Risks Model

A resource-efficient approach to making inferences about the distributional properties of the failure times in a competing risks setting is presented. Efficiency is gained by observing recurrences of the compet- ing risks over a random monitoring period. The resulting model is called the recurrent competing risks model (RCRM) and is coupled with two repair strategies whenever the system fails. ...

Bayesian Nonparametric Inference for Nonhomogeneous Poisson Processes

Several classes of nonparametric priors are employed to model the rate of occurrence of failures of the nonhomogeneous Poisson process used in software reliability or in repairable systems. The classes include the gamma process prior, the beta process prior, and the extended gamma process prior. We derive the posterior distribution for each process. Sampling based methods are developed for Baye...

Nonparametric estimation with left truncated semi-competing risks data

SUMMARY Cause-specific hazard and cumulative incidence function are of practical importance in competing risks studies. Inferential procedures for these quantities are well developed and can be applied to semi-competing risks data, where a terminating event censors a non-terminating event, after coercing the data into the competing risks format. Complications arise when there is left truncation...