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`par` = fit3( x=`x`, y=`y`, start=`start`,
step=`step`, f=`funcname` [, err=`errors`,
ithresh=`ithresh`, sthresh=`sthresh`, nithresh=`nithresh`]
[, /vocal])

Seeks parameters

such that
`par`

is as small as
possible, using the Simplex algorithm. `funcname`(`par`, `x`, `y`)

specifies
the startup values for the parameters. `start`

specifies
the initial step size for each of the parameters, for searching for
the minimum. `step`

must be a `funcname``string`

that names
the user-defined function to call to obtain the quality of the fit.
This function is assumed to return the sum of the square of the
residuals between the data and the model for the current set of
parameters.

specifies the maximum number of search iterations
that is done. It defaults to 0, which corresponds to no iteration
limit.
`ithresh`

The search algorithm searches a certain volume of parameter space for
the minimum. During every iteration it updates the vertex
corresponding to the greatest function value, to home in on the
location of the minimum.

specifies below which
size of the search volume the iteration should stop. The used measure
is the root-mean-square distance of all vertices from the center of
the search volume. This size may increase or decrease, and need not
end up at zero.
`sthresh`

If the best fit does not improve for more than

consecutive search iterations, then the iteration stops. A value of 0
corresponds to no limit. It defaults to 10 times the number of
parameters.
`nithresh`

Upon exit, the last element of `par` contains the standard
deviation of the difference between

and
`y`

. If
`funcname`(`par`, `x`, `y`)

is specified, then the estimated standard errors
on the parameters are returned in it.
`errors`

If `/vocal`

is specified, then about every 2 seconds a line is
printed that lists (1) the iteration number, (2) the residual standard
error of the current best fit, (3) the difference with the previously
printed residual standard error, (4) a measure of the linear size of
the multidimensional volume that is being considered, (5) the
difference with the previously printed size, (6) the current best
values for the first few parameters that have a non-zero step size.

See also: fit

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