Estimate BoxJenkins polynomial model using time domain data
sys = bj(data, [nb
nc nd nf nk])
sys = bj(data,[nb
nc nd nf nk], Name,Value)
sys = bj(data, init_sys)
sys = bj(data, ___, opt)
estimates a BoxJenkins polynomial
model, sys
= bj(data
, [nb
nc nd nf nk]
)sys
, using the timedomain data, data
. [nb
nc nd nf nk]
define the orders of the polynomials used
for estimation.
estimates
a polynomial model with additional options specified by one or more sys
= bj(data
,[nb
nc nd nf nk]
, Name,Value
)Name,Value
pair
arguments.
estimates
a BoxJenkins polynomial using the polynomial model sys
= bj(data
, init_sys
)init_sys
to
configure the initial parameterization of sys
.
estimates
a BoxJenkins polynomial using the option set, sys
= bj(data
, ___, opt
)opt
,
to specify estimation behavior.

Estimation data.
You cannot use frequencydomain data for estimating BoxJenkins models. 

A vector of matrices containing the orders and delays of the BoxJenkins model. Matrices must contain nonnegative integers.


Estimation options.
Use 

Polynomial model that configures the initial parameterization
of
Use the To specify an initial guess for, say, the C(q)
term of To specify constraints for, say, the B(q)
term of
You can similarly specify the initial guess and constraints for the other polynomials. 
Specify optional
commaseparated pairs of Name,Value
arguments. Name
is
the argument name and Value
is the corresponding value.
Name
must appear inside single quotes (' '
). You can
specify several name and value pair arguments in any order as
Name1,Value1,...,NameN,ValueN
.

Input delays. For a system with Default: 0 for all input channels 

Transport delays. Specify transport delays as integers denoting delay of a multiple
of the sample time For a MIMO system with Default: 0 for all input/output pairs 

Logical specifying integrators in the noise channel.
Setting $$y(t)=\frac{B(q)}{F(q)}u(tnk)+\frac{C(q)}{D(q)}\frac{e(t)}{1{q}^{1}}$$ Where, $$\frac{1}{1{q}^{1}}$$ is the integrator in the noise channel,e(t). Default: 

BJ model that fits the estimation data, returned as a discretetime Information about the estimation results and options used is
stored in the
For more information on using 
To estimate a continuoustime model, use:
[1] Ljung, L. System Identification: Theory for the User, Upper Saddle River, NJ, PrenticeHall PTR, 1999.
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