function resid(varargin)
    
//  plot residual analysis
//  
//  Calling Sequence
//  resid(plantData,sys)
//  Parameters
//  plantData : iddata type or nx2 matrix
//  sys : idpoly type polynomial
//  Description
//  resid function compute the residuals of the model with its plant data by taking auto-correlation of the one step ahead prediction error and cross-correlations
//  in between with one step ahead prediction error with plant input.  	
//  Examples
//  a = [1 0.2];b = [0 0.2 0.3];
//  sys = idpoly(a,b,'Ts',0.1)
//  u = idinput(1024,'PRBS',[0 1/20],[-1 1])
//  y = sim(u,sys)+rand(1024,1)
//  plantData = iddata(y,u,0.1)
//  resid(plantData,sys)
//  Authors
//  Ashutosh Kumar Bhargava  

    [lhs rhs] = argn(0)
    //  Checking the number of inputs
    if rhs <> 2 then
        error(msprintf(gettext("%s:Wrong number of input arguments.\n"),"resid"))
    end
    //  Checking the type of first argument
    if typeof(varargin(1)) <> 'constant' && typeof(varargin(1)) <> 'iddata' then
        error(msprintf(gettext("%s:Incompatible model data.\n"),"resid"))
    end
    //  checking the type of second argument
    if typeof(varargin(2)) <> 'idpoly' then
        error(msprintf(gettext("%s:Wrong type for second argument,""idpoly"" type expected.\n"),"resid"))
    end
    //  checking the input dimensions
    yData = []
    uData = []
    tempData = varargin(1)
    if typeof(varargin(1)) == 'iddata' then
        yData = tempData.OutputData
        uData = tempData.InputData
        if ~size(yData,'*') || ~size(uData,'*') then
            error(msprintf(gettext("%s:Model input and output numbers must be equal to the plant data.\n"),"resid"))
        end
    elseif typeof(varargin(1)) == 'constant'then
        if isrow(tempData) || iscolumn(tempData) || length(size(tempData)) <> 2 || size(tempData,'c') <> 2 then
            error(msprintf(gettext("%s:Model input and output numbers must be equal to the plant data.\n"),"resid"))
        end
        yData = tempData(:,1)
        uData = tempData(:,2)
        tempData = iddata(yData,uData,varargin(2).Ts)
    end
    
    //  [a,b,c] = compare(tempData,varargin(2))
    [a,x0] = pe(tempData,varargin(2))
//  ------------------------------------------------------------------------------
    errorData = a
    eAutoCorr = xcorr(errorData,25,'coeff')//  'biased')
    uAutoCorr = xcorr(uData,25,'coeff')//  'biased')
    eAutoCorrMax = max(eAutoCorr)
    eAutoCorr = eAutoCorr/eAutoCorrMax
//  ------------------------------------------------------------------------------
    
    //  confidence interval
    coi1 = 2.58/sqrt(length(yData))
    rect = [0;coi1;25;2*coi1];
    //  disp(rect)
    subplot(2,1,1);
    xrects(rect,7)
    stem([0:25]',eAutoCorr(26:length(eAutoCorr)),5)
    xrect(rect)
    coi2 = 2.58*sqrt(eAutoCorrMax+2*(eAutoCorr(27:50)'*uAutoCorr(27:50)*eAutoCorrMax))/sqrt(length(yData))
    rect = [-25;coi2;50;2*coi2];
    euCrossCorr = xcorr(errorData,uData,25,'biased')
    //  pause
    xtitle('Autocorrelation of Residuals','lag')
    subplot(2,1,2);
    xrects(rect,7)
    //  disp(rect)
    stem([-25:25]',euCrossCorr,5)
    xrect(rect)
    xtitle('Crosscorrelation of Residuals and Input','lag')
    //  figure
    //  plot2d3(euCrossCorr)
endfunction