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What is the prediction difference between the parametric GBLUP and the semi-parametric RKHS models?
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It is also clear that the amount of data that will be needed to resolve each of the regions is still difficult to estimate due to the large differences between the parametric and nonparametric simulation results.
Several elements of the experimental design are likely to have an appreciable contribution to the difference between our parametric and nonparametric simulation results.
Differences between the non-parametric, continuous parameters assessed at study inclusion and at 12-month follow-up visit were compared by the Wilcoxon rank-sum test.
Where parametric statistics have been used there were no differences between the results of parametric and non-parametric analyzes.
The difference between parametric and nonparametric IRT models is the way in which they define the shape of these cumulative IRFs.
Thus while the analysis was based on the assumption of normal distribution, by considering the Pearson coefficient, occurrence of any differences between the results of parametric and non-parametric analysis was also noted.
Nonetheless, as explained earlier in this article, while the analysis was based on the assumption of normal distribution, by considering the Pearson coefficient, occurrence of any differences between the results of parametric and non-parametric analysis was also noted.
Our parametric simulations with the same distribution of missing data than the original regional alignments show that missing data in our regional alignments has an effect, yet it explains only a small fraction of the difference between parametric and nonparametric simulations.
We also computed an overall impact score by assigning a ranking order to the product of the two factors (extent and importance) giving an overall impact scale from 1 to 9. Due to relatively large sample size and normal distribution we anticipated there would not be any difference between results of parametric and corresponding non-parametric tests; this was in fact the case.
The main difference between parametric empirical Bayes (PEB) and nonparametric empirical Bayes (NPEB) is the way in which f 1 and f 2 are treated.
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