statset
statistics: options = statset ()
statistics: options = statset (funcname)
statistics: options = statset (name, value, …)
statistics: options = statset (oldopts, name, value, …)
statistics: options = statset (oldopts, newopts)
statistics: statset ()
Create or modify an options structure for iterative statistics algorithms.
options = statset () returns a structure carrying every
recognized option name, each set to an empty value. An empty option means
"use the calling function's own default", so an all-empty structure
changes nothing wherever it is passed.
options = statset (funcname) returns the options that
funcname uses by default, with the remaining fields left empty.
funcname must name a function of this package that documents an
"Options" argument; see the list below. Unlike the name/value
forms, this form takes no further arguments.
options = statset (name, value, …) returns an
otherwise empty structure with the named options set. Option names are
matched case-insensitively and must be given in full.
options = statset (oldopts, name, value,
…) copies oldopts and applies the given name/value pairs to the
copy. oldopts is left unchanged.
options = statset (oldopts, newopts) merges two
structures: every non-empty field of newopts overrides its
counterpart in oldopts, while an empty field of newopts leaves
the oldopts value in place. Fields that are not recognized option
names are ignored in both structures.
statset () called with no output argument displays the recognized
option names together with their permitted values, marking each default
in braces.
The recognized options are:
| Option | Description |
|---|---|
"Display" | Level of reporting: "off",
"final", or "iter". |
"MaxFunEvals" | Maximum number of objective function evaluations, a positive scalar. |
"MaxIter" | Maximum number of iterations, a positive scalar. |
"TolBnd" | Positive scalar tolerance on parameter bounds. |
"TolFun" | Positive scalar tolerance on the objective function value. |
"TolTypeFun" | Whether "TolFun" is absolute,
"abs", or relative, "rel". |
"TolX" | Positive scalar tolerance on the parameters. |
"TolTypeX" | Whether "TolX" is absolute,
"abs", or relative, "rel". |
"GradObj" | Whether the objective function returns a
gradient, "off" or "on". |
"Jacobian" | Whether the model function returns a Jacobian,
"off" or "on". |
"DerivStep" | Relative step size for finite-difference derivatives, a positive scalar or vector. |
"FunValCheck" | Whether to check the objective function for
invalid values, "off" or "on". |
"Robust" | Whether to invoke a robust fit, "off" or
"on". Superseded by "RobustWgtFun". |
"RobustWgtFun" | Weight function for robust fitting: one of
"andrews", "bisquare", "cauchy", "fair",
"huber", "logistic", "talwar", "welsch", a
function handle, or empty for a non-robust fit. |
"WgtFun" | Weight function used with "Robust".
Superseded by "RobustWgtFun". |
"Tune" | Positive tuning constant for the robust weight function. Set automatically for a named weight function; required for a function handle. |
"UseParallel" | Logical flag requesting parallel computation. |
"UseSubstreams" | Logical flag requesting reproducible random substreams. |
"Streams" | A random stream or a cell array of them. |
"OutputFcn" | A function handle, or a cell array of them, called after each iteration. |
Source Code: statset
funcname may name any of the following functions, each of which
documents an "Options" argument: copulafit, coxphfit,
crossval, evfit, factoran, fitcox,
fitglm, fitglme, fitlme,
fitlmematrix, fitnlm, gamfit, gevfit,
glmfit, gmdistribution, gpfit, kmeans,
kmedoids, lasso, lassoglm, lognfit,
mdscale, mlecov, mlecustom, mvncdf,
mvtcdf, nbinfit, nlinfit, nnmf, normfit,
pca, plsregress, ppca, rocmetrics, tsne,
wblfit, GeneralizedLinearMixedModel, and
LinearMixedModel.
Any function accepting an "Options" argument also accepts a plain
structure carrying only the fields it needs, so statset is a
convenience rather than a requirement.
MATLAB’s statset additionally accepts the names of functions this
package does not provide. Those names are rejected here rather than
answered, since returning options for an absent function would assert a
capability that does not exist.
See also: statget, nlinfit, fitnlm, nnmf, mdscale, ppca, tsne, kmedoids
Source Code: statset
The default options of a given function
options = statset ('nlinfit')
options =
scalar structure containing the fields:
Display = off
MaxFunEvals = [](0x0)
MaxIter = 200
TolBnd = [](0x0)
TolFun = 1.0000e-08
TolTypeFun = [](0x0)
TolX = 1.0000e-08
TolTypeX = [](0x0)
GradObj = [](0x0)
Jacobian = [](0x0)
DerivStep = 6.0555e-06
FunValCheck = on
Robust = off
RobustWgtFun = [](0x0)
WgtFun = bisquare
Tune = [](0x0)
UseParallel = [](0x0)
UseSubstreams = [](0x0)
Streams = {}(0x0)
OutputFcn = [](0x0)
Raise the iteration limit of an existing options structure
options = statset ('nlinfit');
options = statset (options, 'MaxIter', 500);
[options.MaxIter, options.TolFun]
ans = 5.0000e+02 1.0000e-08