%0 Journal Article %1 citeulike:4544266 %A Antoch, J. %D 1998 %J Computational Statistics & Data Analysis %K computer-science %N 4 %P 487--495 %R 10.1016/S0167-9473(98)80002-9 %T Revisiting the pseudorandom number generator ran1 from the NUMERICAL RECIPES %U http://dx.doi.org/10.1016/S0167-9473(98)80002-9 %V 27 %X In this contribution we show the danger which can arise from the use of the pseudorandom number generator ran1 (and partially ran2 as well) from the first edition of the monograph Numerical Recipes in C for some Monte Carlo simulations. This paper complements the paper of Baker (1997) published in SSN in CSDA recently. We show experimentally that the main problem is not in the implementation of these generators but in “their definition”. Two examples show what can happen when we try to establish critical values through simulations basing the necessary calculations on these generators. The third example, “casting doubts on the validity of the central limit theorem”, demonstrates another dangerous situation. Finally, a fourth example shows the high sensitivity of the random number generators studied to changes of the constants defining them. These examples again clearly show the imperative need to check pseudorandom generators before their use, as we do (or at least as we should do) with the theorems we apply. Moreover, it warns against the blind belief in the not-always-valid Czech proverb that … What is written is given .

@article{citeulike:4544266, abstract = {In this contribution we show the danger which can arise from the use of the pseudorandom number generator ran1 (and partially ran2 as well) from the first edition of the monograph Numerical Recipes in C for some Monte Carlo simulations. This paper complements the paper of Baker (1997) published in SSN in CSDA recently. We show experimentally that the main problem is not in the implementation of these generators but in “their definition”. Two examples show what can happen when we try to establish critical values through simulations basing the necessary calculations on these generators. The third example, “casting doubts on the validity of the central limit theorem”, demonstrates another dangerous situation. Finally, a fourth example shows the high sensitivity of the random number generators studied to changes of the constants defining them. These examples again clearly show the imperative need to check pseudorandom generators before their use, as we do (or at least as we should do) with the theorems we apply. Moreover, it warns against the blind belief in the not-always-valid Czech proverb that … What is written is given .}, added-at = {2009-05-19T18:00:18.000+0200}, author = {Antoch, J.}, biburl = {https://www.bibsonomy.org/bibtex/2fee89a300999a1332611c3b27b4fa05b/earthfare}, citeulike-article-id = {4544266}, description = {CiteULike: Everyone's library}, doi = {10.1016/S0167-9473(98)80002-9}, interhash = {8e77d9732d8168ad4e49de1be223ada1}, intrahash = {fee89a300999a1332611c3b27b4fa05b}, issn = {01679473}, journal = {Computational Statistics \& Data Analysis}, keywords = {computer-science}, month = {June}, number = 4, pages = {487--495}, posted-at = {2009-05-19 05:28:03}, priority = {2}, timestamp = {2009-05-19T18:03:27.000+0200}, title = {Revisiting the pseudorandom number generator ran1 from the NUMERICAL RECIPES}, url = {http://dx.doi.org/10.1016/S0167-9473(98)80002-9}, volume = 27, year = 1998 }