Latent diffusion models for survival analysis
From MaRDI portal
Publication:453270
DOI10.3150/09-BEJ217zbMath1323.60106arXiv1010.1688OpenAlexW3102329642WikidataQ62109478 ScholiaQ62109478MaRDI QIDQ453270
Laura M. Sangalli, Gareth O. Roberts
Publication date: 19 September 2012
Published in: Bernoulli (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1010.1688
Bayesian inference (62F15) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Diffusion processes (60J60) Applications of renewal theory (reliability, demand theory, etc.) (60K10) Reliability and life testing (62N05)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A general framework for the parametrization of hierarchical models
- On a class of Bayesian nonparametric estimates. II: Hazard rate estimates
- Nonparametric Bayes estimators based on beta processes in models for life history data
- Survival and event history analysis. A process point of view
- A Bayesian nonparametric approach to reliability
- A random-walk model of human mortality and aging
- Bayesian nonparametric estimation based on censored data
- Understanding the shape of the hazard rate: A process point of view. (With comments and a rejoinder).
- Survival models based on the Ornstein-Uhlenbeck process
- Tailfree and neutral random probabilities and their posterior distributions
- Prior distributions on spaces of probability measures
- Multidimensional diffusion processes.
- On inference for partially observed nonlinear diffusion models using the Metropolis-Hastings algorithm
- Testing Goodness of Fit for Proportional Hazards Model with Censored Observations
- Exact and Computationally Efficient Likelihood-Based Estimation for Discretely Observed Diffusion Processes (with Discussion)
- Survival functions induced by stochastic covariate processes
- Nonparametric Bayesian Estimation of Survival Curves from Incomplete Observations
- Likelihood analysis of non-Gaussian measurement time series
- A Bayesian Non‐parametric Comparison of Two Treatments
- Frailty models based on Lévy processes
- Proportional Hazards Estimate of the Conditional Survival Function
- Likelihood Inference for Discretely Observed Nonlinear Diffusions
- Efficient parametrisations for normal linear mixed models
- A generalized Wilcoxon test for comparing arbitrarily singly-censored samples
- Computational Methods for Multiplicative Intensity Models Using Weighted Gamma Processes
