MATLAB: How can predict multi step ahead using Narnet

Deep Learning Toolboxmachine learningnarnetneural networkprediction

I want to predict the future prices, I have used only the daily historical prices as input. I can predict only one step ahead using this code:
clear all;
clear all;
load('prices.mat'); 
set_size = 1413;
targetSeries =prices(1:set_size);  
targetSeries = targetSeries';
targetSeries_train = targetSeries(1:set_size * (4/5)     );
targetSeries_test  = targetSeries(set_size   * (4/5): end);
targetSeries_train = num2cell(targetSeries_train);
targetSeries_test = num2cell(targetSeries_test);
feedbackDelays = 1:4;
hiddenLayerSize = 10;
net = narnet(feedbackDelays, hiddenLayerSize);
net.inputs{1}.processFcns = {'removeconstantrows','mapminmax'};
[inputs,    inputStates, layerStates,targets] = preparets(net,{},{},     targetSeries_train);
[inputs_test,inputStates_test,layerStates_test,targets_test] = preparets(net,{},{},targetSeries_test);
net.trainFcn = 'trainrp';  % Levenberg-Marquardt
net.performFcn = 'mse';  % Mean squared error
net.plotFcns = {'plotperform','plottrainstate','plotresponse', ...
'ploterrcorr', 'plotinerrcorr'};
[net,tr] = train(net,inputs,targets,inputStates,layerStates);
outputs     = net(inputs_test,inputStates_test,layerStates_test);
errors      = gsubtract(targets_test,outputs);
performance = perform(net,targets_test,outputs)
view(net)
%  netc = closeloop(net);
%  [xc,xic,aic,tc] = preparets(netc,{},{},targetSeries_test);
%  yc = netc(xc,xic,aic);
%  perfc = perform(net,tc,yc)
% nets = removedelay(net);
% [xs,xis,ais,ts] = preparets(nets,{},{},targetSeries_test);
% ys = nets(xs,xis,ais);
% stepAheadPerformance = perform(net,ts,ys)
how I can predict multistep ahead, for example the prediction of 10 days in advance.
Thanks in advance.

Best Answer

Take a look at the line where I define Ypred here I specify nans for the number of forecasts I want to make. I specify 4 more for pre-samples. Hope this helps. And ofcourse Y is your data Ypred are the forecasts
net = narnet(1:4,10);
net.trainParam.showWindow = false;
T = tonndata(Y,false,false);
[Xs,Xi,Ai,Ts] = preparets(net,{},{},T);
net = closeloop(train(net,Xs,Ts,Xi,Ai));
Ypred = nan(14,1);
Ypred = tonndata(Ypred,false,false);
Ypred(1:4) = T(end-3:end);
[xc,xic,aic,tc] = preparets(net,{},{},Ypred);
Ypred = fromnndata(net(xc,xic,aic),true,false,false);
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