論文

査読有り
2008年2月

Parameter estimation and model selection for Neyman-Scott point processes

BIOMETRICAL JOURNAL
  • Ushio Tanaka
  • ,
  • Yosihiko Ogata
  • ,
  • Dietrich Stoyan

50
1
開始ページ
43
終了ページ
57
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1002/bimj.200610339
出版者・発行元
WILEY-V C H VERLAG GMBH

This paper proposes an approximative method for maximum likelihood estimation of parameters of Neyman-Scott and similar point processes. It is based on the point pattern resulting from forming all difference points of pairs of points in the window of observation. The intensity function of this constructed point process can be expressed in terms of second-order characteristics of the original process. This opens the way to parameter estimation, if the difference pattern is treated as a non-homogeneous Poisson process. The computational feasibility and accuracy of this approach is examined by means of simulated data. Furthermore, the method is applied to two biological data sets. For these data, various cluster process models are considered and compared with respect to their goodness-of-fit.

Web of Science ® 被引用回数 : 49

リンク情報
DOI
https://doi.org/10.1002/bimj.200610339
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000253745200003&DestApp=WOS_CPL

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