Poisson superposition processes

نویسندگان

  • Harry Crane
  • Peter McCullagh
چکیده

Superposition is a mapping on point configurations that sends the n-tuple (x1, . . . , xn) ∈ X into the n-point configuration {x1, . . . , xn} ⊂ X , counted with multiplicity. It is an additive set operation such the superposition of a k-point configuration in X is a kn-point configuration in X . A Poisson superposition process is the superposition in X of a Poisson process in the space of finite-length X -valued sequences. From properties of Poisson processes as well as some algebraic properties of formal power series, we obtain an explicit expression for the Janossy measure of Poisson superposition processes, and we study their law under domain restriction. Examples of well-known Poisson superposition processes include compound Poisson, negative binomial, and permanental (boson) processes.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

2 Harry Crane and

Superposition is a mapping on point configurations that sends the n-tuple (x1, . . . , xn) ∈ X into the n-point configuration {x1, . . . , xn} ⊂ X , counted with multiplicity. It is an additive set operation such the superposition of a k-point configuration in X is a kn-point configuration in X . A Poisson superposition process is the superposition in X of a Poisson process in the space of fini...

متن کامل

Poisson process approximation for dependent superposition of point processes

Although the study of weak convergence of superpositions of point processes to the Poisson process dates back to the work of Grigelionis in 1963, it was only recently that Schuhmacher [Stochastic Process. Appl. 115 (2005) 1819–1837] obtained error bounds for the weak convergence. Schuhmacher considered dependent superposition, truncated the individual point processes to 0–1 point processes and ...

متن کامل

Bayesian Computation for the Superposition of Nonhomogeneous Poisson Processes

Bayesian inference for the superposition of nonhomogeneous Poisson processes is studied. A Markov chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, we introduce a latent variable that indicates which component of the superposition model gives rise to the failure. This data augmentation approach fa...

متن کامل

Bayesian Computation for the Superposition ofNonhomogeneous Poisson

Bayesian inference for the superposition of nonhomogeneous Poisson processes is studied. A Markov chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, a latent variable is introduced that indicates which component of the superposition model gives rise to the failure. This data augmentation approach f...

متن کامل

Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling

We develop dependent hierarchical normalized random measures and apply them to dynamic topic modeling. The dependency arises via superposition, subsampling and point transition on the underlying Poisson processes of these measures. The measures used include normalised generalised Gamma processes that demonstrate power law properties, unlike Dirichlet processes used previously in dynamic topic m...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • J. Applied Probability

دوره 52  شماره 

صفحات  -

تاریخ انتشار 2015