diff options
author | Joe Hunkeler <jhunkeler@gmail.com> | 2015-08-11 16:51:37 -0400 |
---|---|---|
committer | Joe Hunkeler <jhunkeler@gmail.com> | 2015-08-11 16:51:37 -0400 |
commit | 40e5a5811c6ffce9b0974e93cdd927cbcf60c157 (patch) | |
tree | 4464880c571602d54f6ae114729bf62a89518057 /math/gsurfit/doc/gserrors.hlp | |
download | iraf-osx-40e5a5811c6ffce9b0974e93cdd927cbcf60c157.tar.gz |
Repatch (from linux) of OSX IRAF
Diffstat (limited to 'math/gsurfit/doc/gserrors.hlp')
-rw-r--r-- | math/gsurfit/doc/gserrors.hlp | 61 |
1 files changed, 61 insertions, 0 deletions
diff --git a/math/gsurfit/doc/gserrors.hlp b/math/gsurfit/doc/gserrors.hlp new file mode 100644 index 00000000..fed9a82e --- /dev/null +++ b/math/gsurfit/doc/gserrors.hlp @@ -0,0 +1,61 @@ +.help gserrors Aug85 "Gsurfit Package" +.ih +NAME +.nf +gserrors -- calculate errors of the coefficients and the chi-square + of the fit +.fi +.ih +SYNOPSIS +gserrors (sf, y, weight, yfit, chi_square, errors) + +.nf +pointer sf # surface descriptor +real y[ARB] # array of data values +real weight[ARB] # array of weights +real yfit[ARB] # array of fitted values +real chi_square # chi_square of fit +real errors[ARB] # array of errors +.fi +.ih +ARGUMENTS +.ls sf +Pointer to the surface descriptor structure. +.le +.ls y +Array of data values. +.le +.ls weight +Array of weights. +.le +.ls yfit +Array of fitted values. +.le +.ls chi_square +The reduced chi-square of the fit. +.le +.ls errors +The array of errors of the coefficients. The number of coefficients +can be obtained by a call to gsstati. +.le + +.nf + nerrors = gsstati (sf, GSNCOEFF) +.fi +.ih +DESCRIPTION +GSCOEFF calculates the reduced chi-square of the fit and the standard +deviation of the coefficients. +The chi-square of the fit is the square root of the sum of the +weighted squares of the residuals divided by the number of degrees +of freedom. If the weights are equal, then the reduced chi-square is +the variance of the fit. The error of the j-th coefficient is the +square root of the j-th diagonal element of the inverse of the data +matrix. If the weights are equal to one, then the errors are scaled +by the square root of the variance of the data. +.ih +NOTES +.ih +SEE ALSO +gscoeff +.endhelp |