Because only visible data are fitted it is assumed in the following examples
that the calling environment has already displayed some data.
 

Fit of Legendre polynomials to an angular distribution

 

FLEG 2 / DEG EVEN 
FIT
FLEG 4 / DEG EVEN
FIT
FRES / CORR
FLIST

 
A Legendre polynomial of second order is defined, with only even terms
and the x-values interpreted as angles in degrees. The fit is executed.
A fourth order term is added and again fitted. Then the results, 
including parameter correlations, and finally the experimental and fit data
are listed 
 

Fit of a single gaussian

 
FWIN                 mark a fit window
FPE * / G            define a Gaussian peak as fit function referring to the fit window
F                    execute fit
FR                   list results
FSUM / T             compute sum and moments of raw data for comparison
 

Fit of Gaussian peaks plus background


FERR / S             define experimental errors to be statistical
FXCAL 0 0.01         decrease x-values in order to avoid overflow
FWIN / LOOP          define a set of windows for background fit by cursor loop
FPOL 8               define background function: polynomial of eighth order
F                    execute fit
FPAR / F             fix all background parameters
FLAST / K            keep last defined function as background
FWIN / ALL           the whole data region is considered by the fit
FPE 10               search for the ten most significant peaks
F                    execute fit
FR 2                 list results of peaks only
FDISP / F(1)         draw background singly
FDISP / P            draw peaks singly
 

Fit of two correlated peaks with relatively fixed parameters

 
FPE 2 / P              enter two peak regions by cursor prompting loop
FPOS 1/ D(2)G(-14.6) R fix the difference of both peak positions;
                       assign a guess value  to peak position 1 less
                       than that of peak 2 by 14.6
FWIDTH 1 / Q(2) G(1) R equate both peak widths and fix the ratio
F / LI                 execute fit giving a  comprehensive output of
                       all iterations, results and correlations
FDI / P                display peaks singly
 

Fit with a user defined function

 
FMY poly               define the user's fit function poly
FPAR 1 / F G(0)        set parameter 1 to zero and fix it
FLAST / K              keep user's function as background
FPE / L                add a Lorentzian function
F                      execute fit
FR                     list results
FDISP / F(1)           draw the user defined function singly