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Subsections


windowize & windowizeNARX

Purpose

Re-arrange the data points into a (block) Hankel matrix for (N)AR(X) time-series modeling

Basic Syntax

>> w = windowize(A, window)
>> [Xw,Yw] = windowizeNARX(X,Y,xdelays, ydelays, steps)

Description

Use windowize function to make a nonlinear AR predictor with a nonlinear regressor. The last elements of the resulting matrix will contain the future values of the time-series, the others will contain the past inputs. window is the relative index of data points in matrix A, that are selected to make a window. Each window is put in a row of matrix W. The matrix W contains as many rows as there are different windows selected in A.

Schematically, this becomes

 >> A = [a1 a2 a3;
         b1 b2 b3;
         c1 c2 c3;
         d1 d2 d3;  
         e1 e2 e3;
         f1 f2 f3;
         g1 g2 g3];

>> W = windowize(A, [1 2 3])

   W = 
     a1 a2 a3  b1 b2 b3  c1 c2 c3
     b1 b2 b3  c1 c2 c3  d1 d2 d3  
     c1 c2 c3  d1 d2 d3  e1 e2 e3  
     d1 d2 d3  e1 e2 e3  f1 f2 f3 
     e1 e2 e3  f1 f2 f3  g1 g2 g3

The function windowizeNARX converts the time-series and his exogeneous variables into a block hankel format useful for training a nonlinear function approximation as a nonlinear ARX model.

Full syntax

See also:

windowizeNARX, predict, trainlssvm, simlssvm


next up previous contents
Next: Bibliography Up: Alphabetical List of Function Previous: validate   Contents
Kristiaan Pelckmans 2003-02-18