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
This note examines the experiment performed by Beaton, Rubin, and Barone (1976) to study the effect ...
Statistical survey has become a very powerful tool for understanding reality and interpreting it and...
Many commonly used data sources in the social sciences suffer from non-random measurement error, und...
Most empirical social scientists are surprised that low-level numerical issues in software can have ...
Numerical issues matter in statistical analysis. Small errors occur when numbers are translated from...
Numerous examples show that some econometric software packages contain serious flaws, and that users...
In this paper we compare the accuracy of three packages that are commonly used for statistical calcu...
This article presents the results of performing the linear and nonlinear used as benchmarks by the N...
Robust statistical methods are designed to work well when classical assumptions, typically normality...
From 1990 to 1993, a series of tests on numerical reliability ofdata analysis systems has been carri...
The measurement and reporting of model error is of basic importance when constructing models. Here, ...
Coding mistakes can lead to false results. Statisticians and data scientists should exploit best pra...
An SPSS script previously presented in this journal contained nontrivial flaws. The script should no...
The numerical reliability of statistical software packages was examined for logistic regression mode...
This paper discusses the numerical precision of five spreadsheets (Calc, Excel, Gnumeric, NeoOffice ...
This note examines the experiment performed by Beaton, Rubin, and Barone (1976) to study the effect ...
Statistical survey has become a very powerful tool for understanding reality and interpreting it and...
Many commonly used data sources in the social sciences suffer from non-random measurement error, und...
Most empirical social scientists are surprised that low-level numerical issues in software can have ...
Numerical issues matter in statistical analysis. Small errors occur when numbers are translated from...
Numerous examples show that some econometric software packages contain serious flaws, and that users...
In this paper we compare the accuracy of three packages that are commonly used for statistical calcu...
This article presents the results of performing the linear and nonlinear used as benchmarks by the N...
Robust statistical methods are designed to work well when classical assumptions, typically normality...
From 1990 to 1993, a series of tests on numerical reliability ofdata analysis systems has been carri...
The measurement and reporting of model error is of basic importance when constructing models. Here, ...
Coding mistakes can lead to false results. Statisticians and data scientists should exploit best pra...
An SPSS script previously presented in this journal contained nontrivial flaws. The script should no...
The numerical reliability of statistical software packages was examined for logistic regression mode...
This paper discusses the numerical precision of five spreadsheets (Calc, Excel, Gnumeric, NeoOffice ...
This note examines the experiment performed by Beaton, Rubin, and Barone (1976) to study the effect ...
Statistical survey has become a very powerful tool for understanding reality and interpreting it and...
Many commonly used data sources in the social sciences suffer from non-random measurement error, und...