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Please note that the recommended version of Scilab is 2026.0.0. This page might be outdated.
See the recommended documentation of this function
armax1
armax identification
Calling Sequence
[arc,resid]=armax1(r,s,q,y,u [,b0f])
Arguments
- y
- output signal 
- u
- input signal 
- r,s,q
- auto regression orders with r >=0, s >=-1. 
- b0f
- optional parameter. Its default value is 0 and it means that the coefficient b0 must be identified. if bof=1 the b0 is supposed to be zero and is not identified 
- arc
- is tlist with type "ar" and fields a, b, d, ny, nu, sig - a
- is the vector - [1,a1,...,a_r]
- b
- is the vector - [b0,......,b_s]
- d
- is the vector - [1,d1,....,d_q]
- sig
- resid=[ sig*echap(1),....,]; 
 
Description
armax1 is used to identify the coefficients of a 1-dimensional ARX process:
A(z^-1)y= B(z^-1)u + D(z^-1)sig*e(t) e(t) is a 1-dimensional white noise with variance 1. A(z)= 1+a1*z+...+a_r*z^r; ( r=0 => A(z)=1) B(z)= b0+b1*z+...+b_s z^s ( s=-1 => B(z)=0) D(z)= 1+d1*z+...+d_q*z^q ( q=0 => D(z)=1)
for the method, see Eykhoff in trends and progress in system identification) page 96. with
z(t)=[y(t-1),..,y(t-r),u(t),..., u(t-s),e(t-1),...,e(t-q)]
and
coef= [-a1,..,-ar,b0,...,b_s,d1,...,d_q]' y(t)= coef'* z(t) + sig*e(t).
a sequential version of the AR estimation where e(t-i) is replaced by an estimated value is used (RLLS). With q=0 this method is exactly a sequential version of armax
Important notice
In Scilab versions up to 4.1.2 the returned value in
    arc.sig is the square of sig
    square. To be conform with the help, the display of arma models
    and the armax function, starting from Scilab-5.0 version the
    returned arc.sig is sig.
Authors
J.-Ph.C; ;
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