svdfittable - linear coefficient fit of a set of basis functions to a dependent column.
SYNOPSYS
svdfittable [-m 'model spec'] column [col ...]
svdfittable fits a set of model functions to the data in column. The
model is a comma separated list of basis functions. svdfittable computes
a linear coefficient for each basis function to provide the best fit sum to
the dependent variable column. Each basis function in the model is
evaluated as an awk expression which may contain table column names and
header values. The columns of the table used in the basis function
expressions are the independent variables of the fit. More than one
dependent variable column may be given and an independent fit will be
performed for each. See slaSvd @{slaSvdcov,
slalib/slaSvdcov.3.html} slaSvdsol
OPTIONS
Provide a model to fit. A comma separated list of basis functions.
A simple linear fit of measured data in column Y to actual position column X.
The first line of the example uses jottable to creates some data to fit. The
second line fits the data with svdfittable and then neatens up the output
table with justify
john@panic : jottable X 5 | column -a Y | compute 'Y = X + gresid(.1)' > foo.tab
john@panic : svdfittable < foo.tab -m '1, X' Y | justify
svdfittable
Model 1, X
RMS for each column fit:
RMS_Y 0.012060
Coefficients for each column fit:
C_Y -0.0646272 0.991883
Y Fit_Y Res_Y
-------- -------- ---------
0.941286 0.927256 -0.014030
1.907160 1.919138 0.011978
2.895200 2.911021 0.015821
3.914360 3.902904 -0.011456
4.897100 4.894787 -0.002313