Bayesian Prediction for Stochastic Processes: Theory and Applications
نویسندگان
چکیده
منابع مشابه
Bayesian prediction for stochastic processes. Theory and applications
In this paper, we adopt a Bayesian point of view for predicting real continuous-time processes. We give two equivalent definitions of a Bayesian predictor and study some properties: admissibility, prediction sufficiency, nonunbiasedness, comparison with efficient predictors. Prediction of Poisson process and prediction of Ornstein-Uhlenbeck process in the continuous and sampled situations are c...
متن کاملBayesian Prediction for Stochastic Processes
In this paper, we adopt a Bayesian point of view for predicting real stochastic processes. We give two equivalent definition of a Bayesian predictor and study some properties: admissibility, prediction sufficiency, unbiasedness, comparison with efficient predictors. Prediction of Poisson process and prediction of Ornstein-Uhlenbeck process in the continuous and sampled situations are considered...
متن کاملBranching Stochastic Processes: History, Theory, Applications
Branching stochastic processes can be considered as models in population dynamics, where the objects have a random lifetime and reproduction following some stochastic laws. Typical examples are nuclear reactions, cell proliferation and biological reproduction, some chemical reactions, economics and financial phenomena. In this survey paper we try to present briefly some of the most important an...
متن کاملExtremal Theory for Stochastic Processes
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your perso...
متن کاملPrediction for Non-Stationary Stochastic Processes – II
A method is presented for extrapolation of time-series which contain time-varying frequency components. The time-series is complex-demodulated at a set of frequencies. The resulting time-frequency time-series are assumed to be time-dependent such that the amplitude and phase change relatively slowly with time. This change is taken into account in the extrapolation. This model of a non-stationar...
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: Sankhya A
سال: 2014
ISSN: 0976-836X,0976-8378
DOI: 10.1007/s13171-014-0059-y