# Difference between revisions of "R-factor"

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− | In GED two types of R-factors are in use: structural R-factor (R<sub>str</sub>, sometimes called just R-factor) and experimental R-factor (R<sub>exp</sub>).<br /> | + | In GED two types of ''R''-factors are in use: structural R-factor (''R<sub>str</sub>'', sometimes called just ''R''-factor) and experimental ''R''-factor (''R<sub>exp</sub>'').<br /> |

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− | '''Structural R-factor''' is a measure of the agreement between the model and the experimental molecular intensity curves, which are traditionally defined either as sM(s) or s<sup>4</sup>I<sub>m</sub>(s). | + | '''Structural ''R''-factor''' is a measure of the agreement between the model and the experimental molecular intensity curves, which are traditionally defined either as ''sM(s)'' or ''s<sup>4</sup>I<sub>m</sub>(s)''. |

In case of using sM(s) molecular intensity curves the structural R-factor in percent units is defined as<br /><br /> | In case of using sM(s) molecular intensity curves the structural R-factor in percent units is defined as<br /><br /> | ||

<math>R_{str} = \sqrt {\frac{\sum_{i}^{N} \sum_{j}^{M} (sM(s)^{m}_{i,j} - sM(s)^{e}_{i,j})^2}{\sum_{i}^N \sum_{j}^M (sM(s)^{e}_{i,j})^2}} \times 100</math><br /><br /> | <math>R_{str} = \sqrt {\frac{\sum_{i}^{N} \sum_{j}^{M} (sM(s)^{m}_{i,j} - sM(s)^{e}_{i,j})^2}{\sum_{i}^N \sum_{j}^M (sM(s)^{e}_{i,j})^2}} \times 100</math><br /><br /> | ||

− | where sM(s)<sup>m</sup> and sM(s)<sup>e</sup> are model and experimental molecular intensity curves and summations are performed over all data points of all sM(s) curves. The smaller R<sub>str</sub> the better agreement between model and experimental data. R<sub>str</sub> usually ranges between 1.0 (small molecules and high quality data) and 10.0% (large molecules or low quality data) and depends on the amount of experimental data. | + | where ''sM(s)<sup>m</sup>'' and ''sM(s)<sup>e</sup>'' are model and experimental molecular intensity curves and summations are performed over all data points of all ''sM(s)'' curves. The smaller ''R<sub>str</sub>'' the better agreement between model and experimental data. ''R<sub>str</sub>'' usually ranges between 1.0 (small molecules and high quality data) and 10.0% (large molecules or low quality data) and depends on the amount of experimental data. |

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+ | ''R<sub>str</sub>'' is equal to ''R<sub>D</sub>'' defined in <bib id="MastersSC2013" /> since it does not account for correlations between values in experimental data. |

## Latest revision as of 10:35, 19 May 2014

In GED two types of *R*-factors are in use: structural R-factor (*R _{str}*, sometimes called just

*R*-factor) and experimental

*R*-factor (

*R*).

_{exp}**Structural**is a measure of the agreement between the model and the experimental molecular intensity curves, which are traditionally defined either as

*R*-factor*sM(s)*or

*s*.

^{4}I_{m}(s)In case of using sM(s) molecular intensity curves the structural R-factor in percent units is defined as

[math]R_{str} = \sqrt {\frac{\sum_{i}^{N} \sum_{j}^{M} (sM(s)^{m}_{i,j} - sM(s)^{e}_{i,j})^2}{\sum_{i}^N \sum_{j}^M (sM(s)^{e}_{i,j})^2}} \times 100[/math]

where *sM(s) ^{m}* and

*sM(s)*are model and experimental molecular intensity curves and summations are performed over all data points of all

^{e}*sM(s)*curves. The smaller

*R*the better agreement between model and experimental data.

_{str}*R*usually ranges between 1.0 (small molecules and high quality data) and 10.0% (large molecules or low quality data) and depends on the amount of experimental data.

_{str}*R _{str}* is equal to

*R*defined in [MastersSC2013]

_{D}**Author:**

*Masters, SarahL.; Atkinson, SandraJ.; Hölbling, Margit; Hassler, Karl*

**Journal:**

*Structural Chemistry*

**Number:**

*4*

**Pages:**

*1201-1206*

**Title:**

*Gas-phase molecular structure of 1,1,1,2-tetrabromo-2,2-dimethyldisilane: theoretical and experimental investigation of a super-halogenated disilane and computational investigation of the F, Cl and I analogues*

**Url:**

*http://dx.doi.org/10.1007/s11224-012-0152-6*

**Volume:**

*24*

**Year:**

*2013*

since it does not account for correlations between values in experimental data.