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author | Joe Hunkeler <jhunkeler@gmail.com> | 2015-08-11 16:51:37 -0400 |
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committer | Joe Hunkeler <jhunkeler@gmail.com> | 2015-08-11 16:51:37 -0400 |
commit | 40e5a5811c6ffce9b0974e93cdd927cbcf60c157 (patch) | |
tree | 4464880c571602d54f6ae114729bf62a89518057 /math/curfit/doc/cvepower.hlp | |
download | iraf-osx-40e5a5811c6ffce9b0974e93cdd927cbcf60c157.tar.gz |
Repatch (from linux) of OSX IRAF
Diffstat (limited to 'math/curfit/doc/cvepower.hlp')
-rw-r--r-- | math/curfit/doc/cvepower.hlp | 55 |
1 files changed, 55 insertions, 0 deletions
diff --git a/math/curfit/doc/cvepower.hlp b/math/curfit/doc/cvepower.hlp new file mode 100644 index 00000000..58e78dae --- /dev/null +++ b/math/curfit/doc/cvepower.hlp @@ -0,0 +1,55 @@ +.help cvepower Jun95 "Curfit Package" +.ih +NAME +cvepower -- compute the errors of the equivalent power series +.ih +SYNOPSIS +cvepower (cv, y, weight, yfit, npts, chisqr, errors) + +.nf +pointer cv # curve descriptor +real y[] # array of y data points +weight weight[] # array of weights +real yfit[] # array of fitted data points +int npts # number of points +real chisqr # the standard deviation of the fit +real errors[] # standard deviations of the power series coefficients +.fi +.ih +ARGUMENTS +.ls cv +Pointer to the curve descriptor structure +.le +.ls y +Array of y data points +.le +.ls yfit +Array of fitted y values +.le +.ls npts +The number of points +.le +.ls chisqr +Reduced chi-squared of the fit. +.le +.ls errors +Array of standard deviations of the equivalent power series coefficients. +.le +.ih +DESCRIPTION +Calculate the reduced chi-squared of the fit and the standard deviation +of the equivalent power series coefficients for fitted Legendre and +Chebyshev polynomials. The errors are rescaled to the equivalent power +series and to the original data range. +.ih +NOTES +The standard deviation 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-squared 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 +SEE ALSO +.endhelp |