R-factors: Difference between revisions
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== Definitions == | == Definitions == | ||
=== Data quality indicators === | === Data quality indicators === | ||
* R<sub>sym</sub> and R<sub>merge</sub> : the formula is | * R<sub>sym</sub> and R<sub>merge</sub> : the formula is | ||
<math> | <math> | ||
R_{merge} = \frac{\sum_{hkl}\vert I_{hkl}-\langle I_{hkl}\rangle\vert}{\sum_{hkl}I_{hkl}} | R_{merge} = \frac{\sum_{hkl}\vert I_{hkl}-\langle I_{hkl}\rangle\vert}{\sum_{hkl}I_{hkl}} | ||
</math> | |||
<br/> | |||
<br/> | |||
<math> | |||
R=\frac{\sum_{hkl_{unique}}\vert F_{hkl}^{(obs)}-F_{hkl}^{(calc)}\vert}{\sum_{hkl_{unique}} F_{hkl}^{(obs)}} | |||
</math> | </math> | ||
* Redundancy-independant version of the above: R<sub>meas</sub> | * Redundancy-independant version of the above: R<sub>meas</sub> | ||
Revision as of 15:51, 14 February 2008
Historically, R-factors were introduced by ...
Definitions
Data quality indicators
- Rsym and Rmerge : the formula is
[math]\displaystyle{
R_{merge} = \frac{\sum_{hkl}\vert I_{hkl}-\langle I_{hkl}\rangle\vert}{\sum_{hkl}I_{hkl}}
}[/math]
[math]\displaystyle{
R=\frac{\sum_{hkl_{unique}}\vert F_{hkl}^{(obs)}-F_{hkl}^{(calc)}\vert}{\sum_{hkl_{unique}} F_{hkl}^{(obs)}}
}[/math]
- Redundancy-independant version of the above: Rmeas
- measuring quality of averaged intensities/amplitudes: Rp.i.m. and Rmrgd-F
Model quality indicators
- R and Rfree : the formula is (LaTex please )
what do R-factors try to measure, and how to interpret their values?
- relative deviation of
Data quality
- typical values: ...
Model quality
what kind of problems exist with these indicators?
- (Rsym / Rmerge ) should not be used, Rmeas should be used instead (explain why ?)
- R/Rfree and NCS: reflections in work and test set are not independant