I am just courious, maybe someone did such error estimation with LabView, and can show me a better approach.
Scenario:
I have the following function with one variable (x), K is a constant:
y = ( -1/2*K + SQRT( 1/4*K^2 - (4*K - K^2)*(x^2 - x) ) ) / (2-1/2*K);
I have x as an input, and I know the error of x at certain positions.
I would like to estimate the error of the result y values from the given x values.
Since this is not a monotonic function (the first derivative changes sign), the standard Gauss error propagation formula with the first partial derivative is not enough here. The first derivative of the above function is simple to
get analytically, but the second would be a pain to calculate...
How would you treate such a problem with LabView, maybe some kind of numerical derivation to get second (or maybe even third derivative from the Taylor series?) derivative?
Right now we just use a more simple error estimation:
we slightly over-estimate the error of y in the following way:
delta_y = MAX { ABS(y(x)-y(x-error)) ; ABS(y(x)-y(x+error)) }So we take the higher difference as an error.
How would you do it differently if you have LabView under your hands? (LabVew pro 2013 + almost all toolkits)
I could not find error calculation related VIs in the drop menu, are there any?
Thanks for any advice!