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  2. Taylor series - Wikipedia

    en.wikipedia.org/wiki/Taylor_series

    Second-order Taylor series approximation (in orange) of a function f (x,y) = e x ln(1 + y) around the origin. In order to compute a second-order Taylor series expansion around point (a, b) = (0, 0) of the function (,) = ⁡ (+), one first computes all the necessary partial derivatives:

  3. Taylor's theorem - Wikipedia

    en.wikipedia.org/wiki/Taylor's_theorem

    In calculus, Taylor's theorem gives an approximation of a -times differentiable function around a given point by a polynomial of degree , called the -th-order Taylor polynomial. For a smooth function , the Taylor polynomial is the truncation at the order k {\textstyle k} of the Taylor series of the function.

  4. Linearization - Wikipedia

    en.wikipedia.org/wiki/Linearization

    The linear approximation of a function is the first order Taylor expansion around the point of interest. In the study of dynamical systems, linearization is a method for assessing the local stability of an equilibrium point of a system of nonlinear differential equations or discrete dynamical systems. [1]

  5. Linear approximation - Wikipedia

    en.wikipedia.org/wiki/Linear_approximation

    Linear approximations in this case are further improved when the second derivative of a, ″ (), is sufficiently small (close to zero) (i.e., at or near an inflection point). If f {\displaystyle f} is concave down in the interval between x {\displaystyle x} and a {\displaystyle a} , the approximation will be an overestimate (since the ...

  6. Affine arithmetic - Wikipedia

    en.wikipedia.org/wiki/Affine_arithmetic

    Affine arithmetic is meant to be an improvement on interval arithmetic (IA), and is similar to generalized interval arithmetic, first-order Taylor arithmetic, the center-slope model, and ellipsoid calculus — in the sense that it is an automatic method to derive first-order guaranteed approximations to general formulas.

  7. Delta method - Wikipedia

    en.wikipedia.org/wiki/Delta_method

    The intuition of the delta method is that any such g function, in a "small enough" range of the function, can be approximated via a first order Taylor series (which is basically a linear function). If the random variable is roughly normal then a linear transformation of it is also normal. Small range can be achieved when approximating the ...

  8. Numerical methods for ordinary differential equations

    en.wikipedia.org/wiki/Numerical_methods_for...

    This class includes Hermite–Obreschkoff methods and Fehlberg methods, as well as methods like the Parker–Sochacki method [17] or Bychkov–Scherbakov method, which compute the coefficients of the Taylor series of the solution y recursively. methods for second order ODEs. We said that all higher-order ODEs can be transformed to first-order ...

  9. Order of approximation - Wikipedia

    en.wikipedia.org/wiki/Order_of_approximation

    First-order approximation is the term scientists use for a slightly better answer. [3] Some simplifying assumptions are made, and when a number is needed, an answer with only one significant figure is often given ("the town has 4 × 10 3, or four thousand, residents"). In the case of a first-order approximation, at least one number given is exact.