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| Author | Marcon, E.; Traissac, S.; Lang, G. | ||||
| 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 |
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| 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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