R-factors

Historically, R-factors were introduced by ...

Definitions

Data quality indicators

• R_sym and R_merge : 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: R_meas
• measuring quality of averaged intensities/amplitudes: R_p.i.m. and R_mrgd-F

Model quality indicators

• R and R_free : 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: ...

what kind of problems exist with these indicators?

- (R_sym / R_merge ) should not be used, R_meas should be used instead (explain why ?)

- R/R_free and NCS: reflections in work and test set are not independant