# _pd_proc_ls_prof_

Names:
'_pd_proc_ls_prof_R_factor' '_pd_proc_ls_prof_wR_factor' '_pd_proc_ls_prof_wR_expected'

Definition:

```   Rietveld/profile fit R factors.

Note that the R factor computed for Rietveld refinements
using the extracted reflection intensity values (often
called the Rietveld or Bragg R factor, R~B~) is not properly
a profile R factor. This R factor may be specified using
_refine_ls_R_I_factor. (Some authors report
_refine_ls_R_Fsqd_factor or _refine_ls_R_factor_all
as the Rietveld or Bragg R factor. While it is appropriate
to compute and report any or all of these R factors,
the names "Rietveld or Bragg R factor" refer strictly to
_refine_ls_R_I_factor.)

_pd_proc_ls_prof_R_factor, often called R~p~, is an
unweighted fitness metric for the agreement between the
observed and computed diffraction patterns.
R~p~ = sum~i~ | I~obs~(i) - I~calc~(i) |
/ sum~i~ ( I~obs~(i) )
_pd_proc_ls_prof_wR_factor, often called R~wp~, is a
weighted fitness metric for the agreement between the
observed and computed diffraction patterns.
R~wp~ = SQRT {
sum~i~ ( w(i) [ I~obs~(i) - I~calc~(i) ]^2^ )
/ sum~i~ ( w(i) [I~obs~(i)]^2^ ) }

_pd_proc_ls_prof_wR_expected, sometimes called the
theoretical R~wp~ or R~exp~, is a weighted fitness metric for
the statistical precision of the data set. For an idealized fit,
where all deviations between the observed intensities and
those computed from the model are due to statistical
fluctuations, the observed R~wp~ should match the expected
R factor. In reality, R~wp~ will always be higher than
R~exp~.
R~exp~ = SQRT {
(n - p)  / sum~i~ ( w(i) [I~obs~(i)]^2^ ) }

Note that in the above equations,
w(i) is the weight for the ith data point (see
_pd_proc_ls_weight).
I~obs~(i) is the observed intensity for the ith data
point, sometimes referred to as y~i~(obs) or
y~oi~. (See _pd_meas_counts_total,
_pd_meas_intensity_total or _pd_proc_intensity_total.)
I~calc~(i) is the computed intensity for the ith data
point with background and other corrections
applied to match the scale of the observed data set,
sometimes referred to as y~i~(calc) or
y~ci~. (See _pd_calc_intensity_total.)
n is the total number of data points (see
_pd_proc_number_of_points) less the number of
data points excluded from the refinement.
p is the total number of refined parameters.

```

The permitted range is 0.0 -> infinity

Type: numb

Category: pd_proc_ls