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  2. Propagation of uncertainty - Wikipedia

    en.wikipedia.org/wiki/Propagation_of_uncertainty

    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 ...

  3. Error analysis (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Error_analysis_(mathematics)

    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. [5] [6]

  4. Euler method - Wikipedia

    en.wikipedia.org/wiki/Euler_method

    The backward Euler method is an implicit method, meaning that the formula for the backward Euler method has + on both sides, so when applying the backward Euler method we have to solve an equation. This makes the implementation more costly.

  5. Error function - Wikipedia

    en.wikipedia.org/wiki/Error_function

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  6. Interval arithmetic - Wikipedia

    en.wikipedia.org/wiki/Interval_arithmetic

    The main objective of interval arithmetic is to provide a simple way of calculating upper and lower bounds of a function's range in one or more variables. These endpoints are not necessarily the true supremum or infimum of a range since the precise calculation of those values can be difficult or impossible; the bounds only need to contain the function's range as a subset.

  7. Aitken's delta-squared process - Wikipedia

    en.wikipedia.org/wiki/Aitken's_delta-squared_process

    In numerical analysis, Aitken's delta-squared process or Aitken extrapolation is a series acceleration method used for accelerating the rate of convergence of a sequence. It is named after Alexander Aitken, who introduced this method in 1926. [1] It is most useful for accelerating the convergence of a sequence that is converging linearly.

  8. Exponential backoff - Wikipedia

    en.wikipedia.org/wiki/Exponential_backoff

    For example, if a smartphone app fails to connect to its server, it might try again 1 second later, then if it fails again, 2 seconds later, then 4, etc. Each time the pause is multiplied by a fixed amount (in this case 2). In this case, the adverse event is failing to connect to the server.

  9. Monte Carlo method - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_method

    For example, consider a quadrant (circular sector) inscribed in a unit square. Given that the ratio of their areas is ⁠ π / 4 ⁠, the value of π can be approximated using the Monte Carlo method: [1] Draw a square, then inscribe a quadrant within it. Uniformly scatter a given number of points over the square.