Difference between revisions of "R-factors"

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== Definitions ==
 
== Definitions ==
 
=== Data quality indicators ===
 
=== Data quality indicators ===
* R<sub>sym</sub> and R<sub>merge</sub> : the formula is (someone with LaTex knowledge please don't hesitate to fill in the formula!)
+
* 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 13:51, 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