On compound Poisson processes arising in change-point type statistical models as limiting likelihood ratios
نویسندگان
چکیده
منابع مشابه
on some bayesian statistical models in actuarial science with emphasis on claim count
چکیده ندارد.
15 صفحه اولBayesian change point estimation in Poisson-based control charts
Precise identification of the time when a process has changed enables process engineers to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for a Poisson process in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step < /div> change, a linear trend and a known multip...
متن کاملOn marginal likelihood computation in change-point models
Change-point models are useful for modeling times series subject to structural breaks. For interpretation and forecasting, it is essential to estimate correctly the number of change points in this class of models. In Bayesian inference, the number of changepoints is typically chosen by the marginal likelihood criterion, computed by Chib’s method. This method requires to select a value in the pa...
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 کاملPoisson processes , ordinary and compound
The Poisson process is a stochastic counting process that arises naturally in a large variety of daily-life situations. We present a few definitions of the Poisson process and discuss several properties as well as relations to some well-known probability distributions. We further briefly discuss the compound Poisson process.
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: Statistical Inference for Stochastic Processes
سال: 2011
ISSN: 1387-0874,1572-9311
DOI: 10.1007/s11203-011-9059-x