compare vs forecast with models
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I'm using ARMA-models to predict a signal. My signal is a timeseries with n points;
input = iddata(signal,[],Ts);
My model is an ARMA-model with p=10 and q=10;
model = armax(input,[10 10]);
After I build my model, I use the compare command to check the performance of my model for 1-step-ahead predictions
[y,fit,xo] = compare(model,input,1);
I also use the forecast command to check the performance of my model
for k = 1:length(input.y)-10
x(k,1) = forecast(model,input.y(k:k+9),1);
end
Both commands check 1-step-ahead forecast, if I'm not mistaken. But when I compare the results from both, they are not equal.
plot(y.y(11:end));
hold on
plot(x);
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/156311/image.jpeg)
So here is my question: How come that compare and forecast give two different answers.
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Fei Deng
2016-9-21
Hi, It is my understanding that you built a ARMA model based on the signal you have and you used function 'compare' and 'forecast' to evaluate the ARAM model. You want the predicted/evaluated output value at time t to be predicted using values in measured output data (input.y) up to time t-1. In order to do that, in the loop you have, change
x(k,1) = forecast(model,input.y(k:k+9),1);
to
x(k,1) = forecast(model,input.y(1:k+9),1);
otherwise, the predicted value at time t will be obtained based on each 10 values in input.y before time t.
If you still don’t get equal results that you expected, here are two suggestions:
1) Check the differences and consider if they are reasonable error by white-noise disturbance value in the model.
2) Consider if the sampling rate is enough for your data.
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