customreg
(Not recommended) Custom regressor for nonlinear ARX models
The customreg command is not recommended. For polynomial
regressors, use polynomialRegressor instead. For other custom regressors, use customRegressor.
For more information, see Version History.
Syntax
C=customreg(Function,Variables)
C=customreg(Function,Variables,Delays,Vectorized)
Description
customreg class represents arbitrary functions
of past inputs and outputs, such as products, powers, and other MATLAB® expressions
of input and output variables.
You can specify custom regressors in addition to or instead of standard regressors for greater flexibility in modeling your data using nonlinear ARX models. For example, you can define regressors like tan(u(t-1)), u(t-1)2, and u(t-1)*y(t-3).
For simpler regressor expressions, specify custom regressors
directly in the app or in the nlarx estimation
command. For more complex expressions, create a customreg object
for each custom regressor and specify these objects as inputs to the
estimation. Regardless of how you specify custom regressors, the toolbox
represents these regressors as customreg objects.
Use getreg to list the expressions
of all standard and custom regressors in your model.
A special case of custom regressors involves polynomial combinations
of past inputs and outputs. For example, it is common to capture nonlinearities
in the system using polynomial expressions like y(t−1)2, u(t−1)2, y(t−2)2,
y(t−1)*y(t−2), y(t−1)*u(t−1), y(t−
2)*u(t−1). At the command
line, use the polyreg command
to generate polynomial-type regressors automatically by computing
all combinations of input and output variables up to a specified degree. polyreg produces customreg objects
that you specify as inputs to the estimation.
The nonlinear ARX model (idnlarx object)
stores all custom regressors as the CustomRegressors property.
You can list all custom regressors using m.CustomRegressors,
where m is a nonlinear ARX model. For MIMO models,
to retrieve the rth custom regressor for output ky,
use m.CustomRegressors{ky}(r).
Use the Vectorized property to specify whether
to compute custom regressors using vectorized form during estimation.
If you know that your regressor formulas can be vectorized, set Vectorized to 1 to
achieve better performance. To better understand vectorization, consider
the custom regressor function handle z=@(x,y)x^2*y. x and y are
vectors and each variable is evaluated over a time grid. Therefore, z must
be evaluated for each (xi,yi) pair, and the results
are concatenated to produce a z vector:
for k = 1:length(x) z(k) = x(k)^2*y(k) end
The above expression is a nonvectorized computation and tends
to be slow. Specifying a Vectorized computation
uses MATLAB vectorization rules to evaluate the regressor expression
using matrices instead of the FOR-loop and results
in faster computation:
% ".*" indicates element-wise operation
z=(x.^2).*y
Construction
C=customreg(Function,Variables)C is
a customreg object that stores custom regressor. Function is
a function of input and output variables. Variables represent
the names of model inputs and outputs in the function Function.
Each input and output name must coincide with the InputName and OutputName properties
of the corresponding idnlarx object.
The size of Variables must match the number
of Function inputs. For multiple-output
models with p outputs, the custom regressor is
a p-by-1 cell array or an array of customreg object,
where the kyth entry defines the custom regressor
for output ky. You must add these regressors to
the model by assigning the CustomRegressors model property
or by using addreg.
C=customreg(Function,Variables,Delays,Vectorized)Arguments. Delays is
a vector of positive integers that represent the delays of Variables variables
(default is 1 for each vector element). The size of Delays must
match the size of Variables. Vectorized value
of 1 uses MATLAB vectorization rules to evaluate
the regressor expression Function. By default, Vectorized value
is 0 (false).
Properties
After creating the object, you can use get or
dot notation to access the object property values. For example:
% List all property values get(C) % Get value of Arguments property C.Arguments
You can also use the set function to set
the value of particular properties. For example:
set(C,'Vectorized',1)| Property Name | Description |
|---|---|
Function | Function handle or character vector representing a function of standards regressors. For example: cr = @(x,y) x*y |
Variables | Cell array of character vectors that represent the names
of model input and output variables in the function For
example, C = customreg(cr,{'y1','u1'},[2 3]) |
Delays | Vector of positive integers representing the delays
of Default: For example, C = customreg(cr,{'y1','u1'},[2 3]) |
Vectorized | Assignable values:
|
