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We used goodness-of-fit tests based on the sum of squared deviations (SSD) and raggedness index (Rag) to test the significance of fit of distribution.
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In Figure 2 we illustrate the empirical overlap length distribution and the best fit of the distribution to an exponential function exp(- ax) with the same mean.
Our model does not force tree reconstructions to fit patterns of distribution in the organismal world (such as distributions of FFs in superkingdoms or organismal groups).
Fitting of distributions was performed using linear regression in MATLAB.
Fits of distributions to sums of two Gaussian functions are shown in blue (R 2 = 0.92).
The result of this analysis was a list of distributional families ranked in terms of the best fit of each distribution to the data (Table 1).
We further calculated the goodness of fit of each distribution as the squared correlation coefficient r between the observed and predicted cumulative distribution functions.
The solid line is a Gaussian fit of the distribution.
However, there are several aspects that can affect the goodness of fit of species distribution models.
The last column presents p-statistic of fit of beta distribution with actual field data.
The plots confirm the excellent fit of this distribution to the data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com