Nonparametric Bayesian inference for multidimensional compound Poisson processes
نویسندگان
چکیده
منابع مشابه
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...
متن کاملBayesian Nonparametric and Parametric Inference
This paper reviews Bayesian Nonparametric methods and discusses how parametric predictive densities can be constructed using nonparametric ideas.
متن کاملExact Statistical Inference for Some Parametric Nonhomogeneous Poisson Processes
Nonhomogeneous Poisson processes (NHPPs) are often used to model recurrent events, and there is thus a need to check model fit for such models. We study the problem of obtaining exact goodness-of-fit tests for certain parametric NHPPs, using a method based on Monte Carlo simulation conditional on sufficient statistics. A closely related way of obtaining exact confidence intervals in parametri...
متن کاملScalable Nonparametric Bayesian Inference on Point Processes with Gaussian Processes
In this paper we propose an efficient, scalable non-parametric Gaussian process model for inference on Poisson point processes. Our model does not resort to gridding the domain or to introducing latent thinning points. Unlike competing models that scale as O(n) over n data points, our model has a complexity O(nk) where k n. We propose a MCMC sampler and show that the model obtained is faster, m...
متن کاملBayesian Nonparametric Poisson Factorization for Recommendation Systems
We develop a Bayesian nonparametric Poisson factorization model for recommendation systems. Poisson factorization implicitly models each user’s limited budget of attention (or money) that allows consumption of only a small subset of the available items. In our Bayesian nonparametric variant, the number of latent components is theoretically unbounded and effectively estimated when computing a po...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Modern Stochastics: Theory and Applications
سال: 2015
ISSN: 2351-6054,2351-6046
DOI: 10.15559/15-vmsta20