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In contrast, model 1 exhibited much worse predictive performance for the 50-mM external validation set with R 0.496 but better R for 100 and two experiments of 300 mM for an external validation set (0.738, 0.766, and 0.869, respectively) (see Fig. 5c, d).
However, our results prove that theoretical arguments in favour of the Laplace prior do have real practical weight, in that the computational advantages with the Gaussian are paid for by a much worse predictive accuracy, and identification needs significantly more measurements than for the Laplace.
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