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. 2023 Apr 11;62(03-04):119–129. doi: 10.1055/a-2048-7692

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The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ )

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.

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Fig. 6 — Run time using the Golub data for various configurations of the high-performance computer. ( A ) Variation of the number of variables included in the simulations for 500 Mock Data Generation (modgo) runs with 250 cores; ( B ) variation of the number of cores for generating 500 modgo datasets with all variables; ( C ) variation of the modgo method (default: estimation of correlation coefficients with polychoric, etc. correlations, calculation of the nearest positive definite matrix, standard tolerance for simulating normally distributed variables; Pearson: estimation of correlation coefficients with Pearson correlations and calculation of the nearest positive definite matrix; high tolerance: estimation of correlation coefficients with polychoric, etc. correlations, without transformation to the nearest positive definite matrix, and high tolerance for simulating normally distributed variables).