Download citation
Download citation
link to html
The usual residual values are complemented by expectation values based solely on the experimental data and the number of model parameters. These theoretical R values serve as benchmark values when all of the basic assumptions for a least-squares refinement, i.e. no systematic errors and a fully adequate model capable of describing the data, are fulfilled. The prediction of R values as presented here is applicable to any field where model parameters are fitted to data with known precision. For crystallographic applications, F2-based residual benchmark values are given. They depend on the first and second moments of variance, intensity and significance distributions, 〈σ2〉, 〈Io2〉, 〈Io22〉. Possible applications of the theoretical R values are, for example, as a data-quality measure or the detection of systematic deviations between experimental data and model predicted data, although the theoretical R values cannot identify the origin of these systematic deviations. The change in R values due to application of a weighting scheme is quantified with the theoretical R values.

Supporting information

pdf

Portable Document Format (PDF) file https://doi.org/10.1107/S0108767313022514/kx5020sup1.pdf
Predicted and published R values, and normal probability plots


Follow Acta Cryst. A
Sign up for e-alerts
Follow Acta Cryst. on Twitter
Follow us on facebook
Sign up for RSS feeds