%0 Book Section %1 Grossfield2009UncertaintySamplingQuality %A Grossfield, Alan %A Zuckerman, Daniel M. %B Annual Reports in Computational Chemistry %D 2009 %E Wheeler, Ralph A. %I Elsevier %K QC analysis error molecular-dynamics quality-control sampling-quality sampling-uncertainty uncertainty uncertainty-quanitfication %P 23 - 48 %R https://doi.org/10.1016/S1574-1400(09)00502-7 %T Chapter 2 Quantifying Uncertainty and Sampling Quality in Biomolecular Simulations %U http://www.sciencedirect.com/science/article/pii/S1574140009005027 %V 5 %X Growing computing capacity and algorithmic advances have facilitated the study of increasingly large biomolecular systems at longer timescales. However, with these larger, more complex systems come questions about the quality of sampling and statistical convergence. What size systems can be sampled fully? If a system is not fully sampled, can certain “fast variables” be considered well converged? How can one determine the statistical significance of observed results? The present review describes statistical tools and the underlying physical ideas necessary to address these questions. Basic definitions and ready-to-use analyses are provided, along with explicit recommendations. Such statistical analyses are of paramount importance in establishing the reliability of simulation data in any given study.

@incollection{Grossfield2009UncertaintySamplingQuality, abstract = {Growing computing capacity and algorithmic advances have facilitated the study of increasingly large biomolecular systems at longer timescales. However, with these larger, more complex systems come questions about the quality of sampling and statistical convergence. What size systems can be sampled fully? If a system is not fully sampled, can certain “fast variables” be considered well converged? How can one determine the statistical significance of observed results? The present review describes statistical tools and the underlying physical ideas necessary to address these questions. Basic definitions and ready-to-use analyses are provided, along with explicit recommendations. Such statistical analyses are of paramount importance in establishing the reliability of simulation data in any given study. }, added-at = {2017-05-03T05:27:55.000+0200}, author = {Grossfield, Alan and Zuckerman, Daniel M.}, biburl = {https://www.bibsonomy.org/bibtex/25a6e5e59c4b1ae4c7c002f76bc4ada52/salotz}, doi = {https://doi.org/10.1016/S1574-1400(09)00502-7}, editor = {Wheeler, Ralph A.}, interhash = {a7ef964f54b5ce1c362b65d0476a9f17}, intrahash = {5a6e5e59c4b1ae4c7c002f76bc4ada52}, issn = {1574-1400}, keywords = {QC analysis error molecular-dynamics quality-control sampling-quality sampling-uncertainty uncertainty uncertainty-quanitfication}, pages = {23 - 48}, publisher = {Elsevier}, series = {Annual Reports in Computational Chemistry }, timestamp = {2017-05-03T05:27:55.000+0200}, title = {Chapter 2 Quantifying Uncertainty and Sampling Quality in Biomolecular Simulations }, url = {http://www.sciencedirect.com/science/article/pii/S1574140009005027}, volume = 5, year = 2009 }