Quadrat Analysis_RW_Thomas

The form of the test described here does not measure

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: ce tests for this property do exist (see Mead, 1974). The main statistical problem with the F test is that once the hypothesis of randomness has been rejected for a single scale the frequency distribution can no longer be assumed to follow the Poisson distribution. Consequently the tests at all other scales become invalid. When this is the case a useful qualitative interpretation of scale effects can be gained from the graph of variance estimates plotted against scales (see fig. 5 (iv)). Nevertheless, the sustained interest of statisticians in the Greig-Smith procedure is an indication of its importance, and recently both Mead (1974) and Zahl (1974) have suggested improvements to the basic method. VI ALTERNATIVE APPROACHES Multinomial coefficients and state descriptions (1) We have seen that the major problem in quadrat analysis is that an observed point pattern contains insufficient information to test all the assumptions of the probability models. This difficulty prompted the author to develop an alternative approach to quadrat analysis based solely on the information contained i...
View Full Document

Ask a homework question - tutors are online