polynomialRegressor
Specify polynomial regressor for nonlinear ARX model
Description
Polynomial regressors are polynomials that are composed of delayed input and
output variables. For example,
y(t–1)2 and
y(t–1) u(t–1)
are both polynomial regressors with orders of 2 and variable delays of one sample. A
polynomialRegressor
object encapsulates a set of polynomial regressors. Use
polynomialRegressor
objects when you create nonlinear ARX models using
idnlarx
or nlarx
. You can specify
polynomialRegressor
objects along with linearRegressor
,
periodicRegressor
,
and customRegressor
objects and combine them into a single combined regressor set.
Creation
Syntax
Description
creates a pReg
= polynomialRegressor(Variables,Lags)polynomialRegressor
object of order 2 that contains output and
input names in Variables and
the corresponding lags in Lags. For
example, if Variables
contains 'y'
and
lags
contains the corresponding lag vector [2
4]
, then the regressors that use 'y'
are
y(t–2)2 and
y(t–4)2.
creates a pReg
= polynomialRegressor(Variables,Lags,Order)polynomialRegressor
object of order Order
.
specifies in pReg
= polynomialRegressor(Variables,Lags,Order,UseAbsolute)UseAbsolute
whether to use the absolute values of the
variables to create the regressors.
specifies in pReg
= polynomialRegressor(Variables,Lags,Order,UseAbsolute,AllowVariableMix)AllowVariableMix
whether to allow multiple variables in
the regressor formulas. For example, if Variables
is equal to
{'y','u'}
, Lags
is equal to
{1,1}
, and Order
is equal to
2
, then a value of true
for
AllowVariableMix
results in the inclusion of the mixed-variable
regressor
y(t–1)u(t–1),
along with the single-variable regressors
y(t–1)2 and
u(t–1)2.
specifies in pReg
= polynomialRegressor(Variables,Lags,Order,UseAbsolute,AllowVariableMix,AllowLagMix)AllowLagMix
whether to allow different lags in the
regressor formulas. For example, if Variables
is equal to
{'y','u'}
, Lags
is equal to {2,[0
3]}
, Order
is equal to 2
, and
AllowVariableMix
is equal to false
, then a value
of true
for AllowLagMix
results in the inclusion
of the mixed-lag regressor
u(t)u(t–3),
along with the unique-lag regressors
y(t–2)2,
u(t)2, and
u(t–3)2. Note that if
you set AllowVariableMix
to true
, then the
regressor set will also include
y(t–2)u(t)
and
y(t–2)u(t–3).
Properties
Examples
Version History
Introduced in R2021a
See Also
idnlarx
| nlarx
| getreg
| linearRegressor
| periodicRegressor
| customRegressor