added scilabs files

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+// Copyright (C) 2015 - IIT Bombay - FOSSEE
+//
+// This file must be used under the terms of the CeCILL.
+// This source file is licensed as described in the file COPYING, which
+// you should have received as part of this distribution.  The terms
+// are also available at
+// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
+// Authors: Harpreet, Ashutosh
+// Organization: FOSSEE, IIT Bombay
+
+function sys =  oe(varargin)
+
+// Estimates Discrete time BJ model
+// y(t) = [B(q)/F(q)]u(t) + [C(q)/D(q)]e(t)
+// Current version uses random initial guess
+// Need to get appropriate guess from OE and noise models
+
+	[lhs , rhs] = argn();	
+	if ( rhs < 2 ) then
+			errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 2"), "oe_2", rhs);
+			error(errmsg)
+	end
+
+
+	z = varargin(1)
+    if typeof(z) == 'iddata' then
+        Ts = z.Ts;unit = z.TimeUnit
+        z = [z.OutputData z.InputData]
+    elseif typeof(z) == 'constant' then
+        Ts = 1;unit = 'seconds'
+    end
+	if ((~size(z,2)==2) & (~size(z,1)==2)) then
+		errmsg = msprintf(gettext("%s: input and output data matrix should be of size (number of data)*2"), "oe_2");
+		error(errmsg);
+	end
+
+	if (~isreal(z)) then
+		errmsg = msprintf(gettext("%s: input and output data matrix should be a real matrix"), "oe_2");
+		error(errmsg);
+	end
+//
+	n = varargin(2)
+	if (size(n,"*")<2| size(n,"*")>3) then
+		errmsg = msprintf(gettext("%s: The order and delay matrix [nb nf nk] should be of size [2 4]"), "oe_2");
+		error(errmsg);
+	end
+
+	if (size(find(n<0),"*") | size(find(((n-floor(n))<%eps)== %f))) then
+		errmsg = msprintf(gettext("%s: values of order and delay matrix [nb nf nk] should be nonnegative integer number "), "oe_2");
+		error(errmsg);
+	end
+//
+	nb= n(1); nf = n(2);
+//	
+	if (size(n,"*") == 2) then
+		nk = 1
+	else
+		nk = n(3);
+	end
+
+    // storing U(k) , y(k) and n data in UDATA,YDATA and NDATA respectively 
+    YDATA = z(:,1);
+    UDATA = z(:,2);
+    NDATA = size(UDATA,"*");
+    function e = G(p,m)
+        e = YDATA - _objoefun(UDATA,YDATA,p,nf,nb,nk);
+    endfunction
+    tempSum = nf+nb
+    p0 = linspace(0.04,0.041,tempSum)';
+    [var,errl] = lsqrsolve(p0,G,size(UDATA,"*"));
+    err = (norm(errl)^2);
+    opt_err = err;
+	resid = G(var,[]);
+    f = poly([1; var(nb+1:nb+nf)],"q","coeff");
+    b = poly([repmat(0,nk,1);var(1:nb)]',"q","coeff");
+    t = idpoly(1,coeff(b),1,1,coeff(f),Ts)
+    
+    // estimating the other parameters
+    [temp1,temp2,temp3] = predict(z,t)
+    [temp11,temp22,temp33] = pe(z,t)
+    
+    estData = calModelPara(temp1,temp11,n(1)+n(2))
+    //pause
+       t.Report.Fit.MSE = estData.MSE 
+       t.Report.Fit.FPE = estData.FPE
+    t.Report.Fit.FitPer = estData.FitPer
+       t.Report.Fit.AIC = estData.AIC
+      t.Report.Fit.AICc = estData.AICc
+      t.Report.Fit.nAIC = estData.nAIC
+       t.Report.Fit.BIC = estData.BIC
+             t.TimeUnit = unit
+                    sys = t
+    //sys = t
+    //sys.TimeUnit = unit
+endfunction
+
+function yhat = _objoefun(UDATA,YDATA,x,nf,nb,nk)
+    x=x(:)
+     q = poly(0,'q')
+    tempSum = nb+nf
+    // making polynomials
+    b = poly([repmat(0,nk,1);x(1:nb)]',"q","coeff");
+    f =  -1*poly([x(nb+1:nb+nf)]',"q","coeff")
+    fSize = coeff(f);bSize = coeff(b)
+    maxDelay = max([length(fSize) length(bSize)])
+    yhat = [YDATA(1:maxDelay)]
+    for k=maxDelay+1:size(UDATA,"*")
+        tempB = 0
+        for ii = 1:size(bSize,'*')
+            tempB = tempB + bSize(ii)*UDATA(k-ii+1)
+        end
+        tempF = 0
+        for ii = 1:size(fSize,"*")
+            tempF = tempF + fSize(ii)*yhat(k-ii)
+        end
+        yhat = [yhat; [ tempB + tempF ]];
+    end
+endfunction