A martingale characterization of the set-indexed poisson process

1994 ◽  
Vol 51 (1-2) ◽  
pp. 69-82 ◽  
Author(s):  
B. Gail Ivanoff ◽  
Ely Merzbach
Keyword(s):  
Poisson Process ◽  
Martingale Characterization

A martingale characterization of mixed Poisson processes

1987 ◽  
Vol 24 (1) ◽  
pp. 246-251 ◽  
Author(s):  
Dietmar Pfeifer ◽  
Ursula Heller
Keyword(s):  
Poisson Process ◽  
Random Variable ◽  
Poisson Processes ◽  
Birth Process ◽  
Mixed Poisson Process ◽  
Martingale Characterization

It is shown that an elementary pure birth process is a mixed Poisson process iff the sequence of post-jump intensities forms a martingale with respect to the σ -fields generated by the jump times of the process. In this case, the post-jump intensities converge almost surely to the mixing random variable of the process.

scholarly journals A martingale characterization of Pólya-Lundberg processes

2006 ◽  
Vol 43 (03) ◽  
pp. 741-754 ◽  
Author(s):  
Birgit Niese
Keyword(s):  
Poisson Process ◽  
Exponential Family ◽  
Exponential Families ◽  
Counting Processes ◽  
Mixed Poisson Process ◽  
Martingale Characterization

We study exponential families within the class of counting processes and show that a mixed Poisson process belongs to an exponential family if and only if it is either a Poisson process or has a gamma structure distribution. This property can be expressed via exponential martingales.

scholarly journals A martingale characterization of Pólya-Lundberg processes

2006 ◽  
Vol 43 (3) ◽  
pp. 741-754 ◽  
Author(s):  
Birgit Niese
Keyword(s):  
Poisson Process ◽  
Exponential Family ◽  
Exponential Families ◽  
Counting Processes ◽  
Mixed Poisson Process ◽  
Martingale Characterization

We study exponential families within the class of counting processes and show that a mixed Poisson process belongs to an exponential family if and only if it is either a Poisson process or has a gamma structure distribution. This property can be expressed via exponential martingales.

An extension of watanabe's theorem of characterization of poisson processes over the positive real half line

1975 ◽  
Vol 12 (2) ◽  
pp. 396-399 ◽  
Author(s):  
P. Bremaud
Keyword(s):  
Poisson Process ◽  
Lebesgue Measure ◽  
Elementary Proof ◽  
Characterization Theorem ◽  
Poisson Processes ◽  
Half Line ◽  
Positive Real ◽  
The Mean ◽  
Martingale Characterization

We give an elementary proof of the martingale characterization theorem for Poisson processes over the positive real half line. This theorem is due to Watanabe [8] in the case where the mean measure associated to the Poisson process is the Lebesgue measure.

A martingale characterization of mixed Poisson processes

1987 ◽  
Vol 24 (01) ◽  
pp. 246-251 ◽  
Author(s):  
Dietmar Pfeifer ◽  
Ursula Heller
Keyword(s):  
Poisson Process ◽  
Random Variable ◽  
Poisson Processes ◽  
Birth Process ◽  
Mixed Poisson Process ◽  
Martingale Characterization

It is shown that an elementary pure birth process is a mixed Poisson process iff the sequence of post-jump intensities forms a martingale with respect to the σ -fields generated by the jump times of the process. In this case, the post-jump intensities converge almost surely to the mixing random variable of the process.

An extension of watanabe's theorem of characterization of poisson processes over the positive real half line

1975 ◽  
Vol 12 (02) ◽  
pp. 396-399 ◽  
Author(s):  
P. Bremaud
Keyword(s):  
Poisson Process ◽  
Lebesgue Measure ◽  
Elementary Proof ◽  
Characterization Theorem ◽  
Poisson Processes ◽  
Half Line ◽  
Positive Real ◽  
The Mean ◽  
Martingale Characterization

We give an elementary proof of the martingale characterization theorem for Poisson processes over the positive real half line. This theorem is due to Watanabe [8] in the case where the mean measure associated to the Poisson process is the Lebesgue measure.

A characterization of the Poisson process

1974 ◽  
Vol 11 (1) ◽  
pp. 72-85 ◽  
Author(s):  
S. M. Samuels
Keyword(s):  
Poisson Process ◽  
Renewal Process ◽  
Poisson Processes ◽  
Renewal Processes ◽  
Sufficient Condition ◽  
Necessary And Sufficient Condition ◽  
Complete Proof ◽  
Necessary And Sufficient

Theorem: A necessary and sufficient condition for the superposition of two ordinary renewal processes to again be a renewal process is that they be Poisson processes.A complete proof of this theorem is given; also it is shown how the theorem follows from the corresponding one for the superposition of two stationary renewal processes.

The coincidence approach to stochastic point processes

1975 ◽  
Vol 7 (1) ◽  
pp. 83-122 ◽  
Author(s):  
Odile Macchi
Keyword(s):  
Poisson Process ◽  
Probability Space ◽  
Point Processes ◽  
Counting Process ◽  
Regular Point ◽  
General Point ◽  
Completely Regular ◽  
Photon Process ◽  
Stochastic Point Processes

The structure of the probability space associated with a general point process, when regarded as a counting process, is reviewed using the coincidence formalism. The rest of the paper is devoted to the class of regular point processes for which all coincidence probabilities admit densities. It is shown that their distribution is completely specified by the system of coincidence densities. The specification formalism is stressed for ‘completely’ regular point processes. A construction theorem gives a characterization of the system of coincidence densities of such a process. It permits the study of most models of point processes. New results on the photon process, a particular type of conditioned Poisson process, are derived. New examples are exhibited, including the Gauss-Poisson process and the ‘fermion’ process that is suitable whenever the points are repulsive.

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