Le 16/01/2013 16:14, Adrien ANDRÉ a écrit : > Hi all, Hi Adrien,
> > does someone know how i could integrate propagation of uncertainty > (https://en.wikipedia.org/wiki/Error_propagation) using something better > organized than Michael Thomas Flanagan's ErrorProp Class > (http://www.ee.ucl.ac.uk/~mflanaga/java/ErrorProp.html)? For now, there is no direct support for this in [math]. However, you may find a basic building block for this by replacing double variables with the new DerivativeStructure class. When you have a function f(x1, x2, ... xn), using DerivativeStructure allows you to get: df/dx1 * delta_1, df/dx2 * delta_2, ... df/dxn * delta_n For the vanilla use of DerivativeStructure, the delta_k values are here because we use them to propagate derivatives using chained function calls: we initialize delta_i with 1 for the innermost function so it represent the independent variables, and then propagate them from function calls to function calls, so when we compute f(g(h(x)))) we really have df/dx at the end, not df/dg. In your case, you can initialize the delta_i with your initial uncertainties instead of 1, so you will really be propagating variances. best regards, Luc > > Regards, > > Adrien > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [email protected] > For additional commands, e-mail: [email protected] > > --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
