
#1
Sep1213, 04:12 AM

P: 1

Hi folks,
I have a rather simple question on error propagation  I have 2 sets of models, where the results from model are used as variables in the next model. I need to know how to carry forward errors from one to another. Case  Model 1: Y = a*exp(b*X) + c The errors on X (which is a vector of about 100 samples) and Y (a vector of same size as X) are not know. From fitting the above nonlinear model to the data and examining the residuals, I can calculate Mean Absolute Error, RMSE, etc. So, in the end I get a vector of Y values and a single error estimate from the model (e.g. RMSE). Model 2: Z = s*(Y)^t + u Where Y is the variable obtained from the results of Model 1. Applying Model 1 to a large number of new X values, I now have Y as a vector with > 10,000 elements. Each element in vector Y should have an associated error. My question is  what error should I give each element of vector Y? My next question is, once the error on each element of vector Y is known, how do I propagate this error to each element of vector Z? Finally, how do I calculate RMSE for Model 2? All help will be much appreciated! Thanks, Yaal 



#2
Sep1213, 08:13 AM

Mentor
P: 16,485

If your process involves nonlinearity and complicated methods then your best bet will be to use some bootstrapping technique to get an estimate of the errors in Z.
http://en.wikipedia.org/wiki/Bootstrapping_(statistics) 



#3
Sep1213, 08:31 AM

P: 1,273

I fixed the broken link. http://en.wikipedia.org/wiki/Bootstrapping_(statistics)




#4
Sep1213, 08:33 AM

Mentor
P: 16,485

Error analysis and propagation
Thanks



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