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Author (up) Marcon, E.; Traissac, S.; Lang, G. pdf  url
doi  openurl
  Title A Statistical Test for Ripley’s Function Rejection of Poisson Null Hypothesis Type Journal Article
  Year 2013 Publication ISRN Ecology Abbreviated Journal ISRN Ecology  
  Volume 2013 Issue Article ID 753475 Pages 9  
  Abstract Ripley’s K function is the classical tool to characterize the spatial structure of point patterns. It is widely used in vegetation studies. Testing its values against a null hypothesis usually relies on Monte-Carlo simulations since little is known about its distribution.
We introduce a statistical test against complete spatial randomness (CSR). The test returns the p-value to reject the null hypothesis of independence between point locations. It is more rigorous and faster than classical Monte-Carlo simulations. We show how to apply it to a tropical forest plot. The necessary R code is provided.
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  Notes Approved no  
  Call Number EcoFoG @ webmaster @ 852 Serial 479  
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