statset
Create statistics options structure
Syntax
statset
statset(statfun)
options = statset(...)
options = statset(fieldname1
,val1
,fieldname2
,val2
,...)
options = statset(oldopts,fieldname1
,val1
,fieldname2
,val2
,...)
options = statset(oldopts,newopts)
Description
statset
with no input arguments
and no output arguments displays all fields of a statistics options
structure and their possible values.
statset(statfun)
displays fields and default values used by the
Statistics and Machine Learning Toolbox™ function statfun
. Specify statfun
using a
character vector, a string scalar, or a function handle.
options = statset(...)
creates
a statistics options structure options
. With no
input arguments, all fields of the options structure are an empty
array ([]
). With a specified statfun
,
function-specific fields are default values and the remaining fields
are []
. Function-specific fields set to []
indicate
that the function is to use its default value for that parameter.
For available options
, see Inputs.
options = statset(
creates an options structure in which the named fields have the specified values. Any
unspecified values are fieldname1
,val1
,fieldname2
,val2
,...)[]
. Use character vectors or string scalars for
field names. For named values, you must input the complete character vector or string scalar
for the value. If you provide an invalid character vector or string scalar for a value,
statset
uses the default.
options = statset(oldopts,
creates
a copy of fieldname1
,val1
,fieldname2
,val2
,...)oldopts
with the named parameters changed
to the specified values.
options = statset(oldopts,newopts)
combines
an existing options structure, oldopts
, with a
new options structure, newopts
. Any parameters
in newopts
with nonempty values overwrite corresponding
parameters in oldopts
.
Input Arguments
|
Relative difference used in finite difference derivative calculations. A positive scalar, or a vector of positive scalars the same size as the vector of parameters estimated by the Statistics and Machine Learning Toolbox function using the options structure. |
|
Amount of information displayed by the algorithm.
|
|
Check for invalid values, such as
|
|
Flags whether the objective function returns a gradient vector as a second output.
|
|
Flags whether the objective function returns a Jacobian as a second output.
|
|
Maximum number of objective function evaluations allowed. Positive integer. |
|
Maximum number of iterations allowed. Positive integer. |
|
The solver calls all output functions after each iteration.
|
|
(Not recommended) Invoke robust fitting option.
|
|
Weight function for robust fitting. Can also be a function
handle that accepts a normalized residual as input and returns the
robust weights as output. If you use a function handle, give a |
|
A single instance of the |
|
Parameter bound tolerance. Positive scalar. |
|
Termination tolerance for the objective function value. Positive scalar. |
|
Use
|
|
Use
|
|
Termination tolerance for the parameters. Positive scalar. |
|
Tuning constant used in robust fitting to normalize the residuals before applying the weight function. The default value depends upon the weight function. This parameter is necessary if you specify the weight function as a function handle. Positive scalar. See Robust Options. |
|
Flag indicating whether eligible functions should use capabilities of the Parallel Computing Toolbox™ (PCT), if the capabilities are available. That is, if the PCT is
installed, and a PCT |
|
Flag indicating whether the random number generator in eligible
functions should use |
|
(Not recommended) Weight function for robust fitting. Valid only when
|
Examples
Suppose you want to change the default parameter values for
the function evfit
, which fits
an extreme value distribution to data. The defaults parameter values
are:
statset('evfit') ans = Display: 'off' MaxFunEvals: [] MaxIter: [] TolBnd: [] TolFun: [] TolTypeFun: [] TolX: 1.0000e-06 TolTypeX: [] GradObj: [] Jacobian: [] DerivStep: [] FunValCheck: [] Robust: [] RobustWgtFun: [] WgtFun: [] Tune: [] UseParallel: [] UseSubstreams: [] Streams: [] OutputFcn: []
The only parameters that evfit
uses are Display
and TolX
.
To create an options structure with the value of TolX
set
to 1e-8
, enter:
options = statset('TolX',1e-8)
% Pass options to evfit
:
mu = 1;
sigma = 1;
data = evrnd(mu,sigma,1,100);
paramhat = evfit(data,[],[],[],options)
More About
Version History
Introduced before R2006a