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The best FP transformation for a variable was identified by comparing the best fitting FP1 with the best-fitting FP2 and choosing that which gave the most significant fit.
This model has a highly significant fit (p = 9.90E-19).
The statistically significant fit, quantitatively expressed in the R2 parameter, is also indicated by relatively low errors of the coefficients in Equation 1.
Although the full model showed a significant fit, there were non-significant terms (p ≥ 0.05) in the model, which were the square terms of KH2PO4 and the interaction terms between NaNO3 and K2HPO4.
It can be seen at the San Diego site none of the generic distributions was found to provide a statistically significant fit for the maximum and Van Aerde methods.
Test statistics, the maximum distance between the empirical CDF (Cumulative Distribution Function) of the shear strength data, and the theoretical CDF of a probability distribution are used as the decision criterion based on significant fit and best fit.
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The probability distributions regarded as significant fits and best fits are decided for each depth.
The statistically significant fitted models were selected based on the higher coefficient of determination (r2) and lower regression standard error (RSE).
Compounds with significant fits to the Hill model using either NLS or WNLS, but not both, are classified as INCONCLUSIVE*[±3].
As far as I see the authors infer that distributions follow scale free power law behavior simply from the fact that the fits are significant and that shuffling of the data do not result in significant fits.
Finally, of the parameter sets that yielded significant fits, using parameters that were individually significant to the model and did not suffer from damaging collinearity, we selected the model with highest R2, also measured using the regstats function.
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