3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Generalized Gamma measures and shot-noise Cox processes

      Advances in Applied Probability
      Cambridge University Press (CUP)

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          A parametric family of completely random measures, which includes gamma random measures, positive stable random measures as well as inverse Gaussian measures, is defined. In order to develop models for clustered point patterns with dependencies between points, the family is used in a shot-noise construction as intensity measures for Cox processes. The resulting Cox processes are of Poisson cluster process type and include Poisson processes and ordinary Neyman-Scott processes.

          Related collections

          Most cited references14

          • Record: found
          • Abstract: not found
          • Article: not found

          Log Gaussian Cox Processes

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Survival models for heterogeneous populations derived from stable distributions

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Poisson/gamma random field models for spatial statistics

              R Wolpert (1998)
                Bookmark

                Author and article information

                Journal
                applab
                Advances in Applied Probability
                Adv. Appl. Probab.
                Cambridge University Press (CUP)
                0001-8678
                1475-6064
                December 1999
                July 2016
                : 31
                : 04
                : 929-953
                Article
                10.1017/S0001867800009538
                c6755283-f77a-4a27-84fe-cc669aff6755
                © 1999
                History

                Comments

                Comment on this article