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  2. Taylor's theorem - Wikipedia

    en.wikipedia.org/wiki/Taylor's_theorem

    v. t. e. 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 of the Taylor series of the function.

  3. Taylor series - Wikipedia

    en.wikipedia.org/wiki/Taylor_series

    The sine function (blue) is closely approximated by its Taylor polynomial of degree 7 (pink) for a full period centered at the origin. The Taylor polynomials for ln(1 + x) only provide accurate approximations in the range −1 < x ≤ 1. For x > 1, Taylor polynomials of higher degree provide worse approximations.

  4. Power series - Wikipedia

    en.wikipedia.org/wiki/Power_series

    The partial sums of a power series are polynomials, the partial sums of the Taylor series of an analytic function are a sequence of converging polynomial approximations to the function at the center, and a converging power series can be seen as a kind of generalized polynomial with infinitely many terms. Conversely, every polynomial is a power ...

  5. Order of approximation - Wikipedia

    en.wikipedia.org/wiki/Order_of_approximation

    In the case of a smooth function, the n th-order approximation is a polynomial of degree n, which is obtained by truncating the Taylor series to this degree. The formal usage of order of approximation corresponds to the omission of some terms of the series used in the expansion. This affects accuracy.

  6. Polynomial interpolation - Wikipedia

    en.wikipedia.org/wiki/Polynomial_interpolation

    In numerical analysis, polynomial interpolation is the interpolation of a given bivariate data set by the polynomial of lowest possible degree that passes through the points of the dataset. [1] Given a set of n + 1 data points , with no two the same, a polynomial function is said to interpolate the data if for each .

  7. Finite difference method - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_method

    Where n! denotes the factorial of n, and R n (x) is a remainder term, denoting the difference between the Taylor polynomial of degree n and the original function. Following is the process to derive an approximation for the first derivative of the function f by first truncating the Taylor polynomial plus remainder: f ( x 0 + h ) = f ( x 0 ) + f ...

  8. Differential calculus - Wikipedia

    en.wikipedia.org/wiki/Differential_calculus

    c should always be ⁠ f''(x 0) / 2 ⁠, and d should always be ⁠ f'''(x 0) / 3! ⁠. Using these coefficients gives the Taylor polynomial of f. The Taylor polynomial of degree d is the polynomial of degree d which best approximates f, and its coefficients can be found by a generalization of the above formulas.

  9. Quadratic function - Wikipedia

    en.wikipedia.org/wiki/Quadratic_function

    Quadratic function. In mathematics, a quadratic function of a single variable is a function of the form [1] where ⁠ ⁠ is its variable, and ⁠ ⁠, ⁠ ⁠, and ⁠ ⁠ are coefficients. The expression ⁠ ⁠, especially when treated as an object in itself rather than as a function, is a quadratic polynomial, a polynomial of degree two.