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Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables (+) = + + (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...
Stability is a measure of the sensitivity to rounding errors of a given numerical procedure; by contrast, the condition number of a function for a given problem indicates the inherent sensitivity of the function to small perturbations in its input and is independent of the implementation used to solve the problem.
The coefficients found by Fehlberg for Formula 1 (derivation with his parameter α 2 =1/3) are given in the table below, using array indexing of base 1 instead of base 0 to be compatible with most computer languages:
This type comes from numerical errors and numerical approximations per implementation of the computer model. Most models are too complicated to solve exactly. For example, the finite element method or finite difference method may be used to approximate the solution of a partial differential equation (which introduces numerical errors).
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When using approximation equations or algorithms, especially when using finitely many digits to represent real numbers (which in theory have infinitely many digits), one of the goals of numerical analysis is to estimate computation errors. [5] Computation errors, also called numerical errors, include both truncation errors and roundoff errors.
Thus, even when using arguably the simplest nonlinear function, the square of a random variable, the process of finding the mean and variance of the derived quantity is difficult, and for more complicated functions it is safe to say that this process is not practical for experimental data analysis.
Suppose we have a continuous differential equation ′ = (,), =, and we wish to compute an approximation of the true solution () at discrete time steps ,, …,.For simplicity, assume the time steps are equally spaced: