accuracy: Tools for Accurate and Reliable Statistical Computing

Micah Altman, Jeff Gill and Michael P. McDonald

Journal of Statistical Software, 2007, vol. 021, issue i01

Abstract: Most empirical social scientists are surprised that low-level numerical issues in software can have deleterious effects on the estimation process. Statistical analyses that appear to be perfectly successful can be invalidated by concealed numerical problems. We have developed a set of tools, contained in accuracy, a package for R and S-PLUS, to diagnose problems stemming from numerical and measurement error and to improve the accuracy of inferences. The tools included in accuracy include a framework for gauging the computational stability of model results, tools for comparing model results, optimization diagnostics, and tools for collecting entropy for true random numbers generation.

Date: 2007-07-25
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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:021:i01

DOI: 10.18637/jss.v021.i01

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