Quadrat Analysis_RW_Thomas

For instance if in our innovation adoption example

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Unformatted text preview: nificantly over the study area, we could observe clustering in the distribution of adopters not because of short distance social contacts between farmers, but because there were high densities of farmers in lowland areas and low densities in upland areas. The not the result of a 'genuine' contagious process. Because these two sets of assumptions lead to the same predicted frequency distribution the design of a quadrat sampling experiment must make clear whether the generalised or compound model is appropriate. The generalised distribution is the more precisely defined model in geographical terms, but for its assumptions to hold the research worker must be confident that both the points and the study area are fairly homogeneous in nature. (iii) Moments and maximum likelihood estimation of k Ideally, when we test the validity of the assumptions of a probability model as an explanation for the processes controlling a point pattern, we should possess sufficient knowledge of these processes to specify the values of the model parameters from a priori reasoning. For example, if we wished to fit the negative binomial to the agricultural innovation problem we s...
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