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  2. Linear least squares - Wikipedia

    en.wikipedia.org/wiki/Linear_least_squares

    Linear least squares (LLS) is the least squares approximation of linear functions to data. It is a set of formulations for solving statistical problems involved in linear regression, including variants for ordinary (unweighted), weighted, and generalized (correlated) residuals.

  3. Numerical methods for linear least squares - Wikipedia

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

    National Physical Laboratory (1961), "Chapter 2: Linear Equations and Matrices: Direct Methods on Automatic Computers", Modern Computing Methods, Notes on Applied Science, vol. 16 (2nd ed.), Her Majesty's Stationery Office

  4. Macaulay's method - Wikipedia

    en.wikipedia.org/wiki/Macaulay's_method

    Macaulay's method (the double integration method) is a technique used in structural analysis to determine the deflection of Euler-Bernoulli beams. Use of Macaulay's ...

  5. Levenberg–Marquardt algorithm - Wikipedia

    en.wikipedia.org/wiki/Levenberg–Marquardt...

    The primary application of the Levenberg–Marquardt algorithm is in the least-squares curve fitting problem: given a set of empirical pairs (,) of independent and dependent variables, find the parameters ⁠ ⁠ of the model curve (,) so that the sum of the squares of the deviations () is minimized:

  6. Powell's dog leg method - Wikipedia

    en.wikipedia.org/wiki/Powell's_dog_leg_method

    Powell's dog leg method, also called Powell's hybrid method, is an iterative optimisation algorithm for the solution of non-linear least squares problems, introduced in 1970 by Michael J. D. Powell. [1] Similarly to the Levenberg–Marquardt algorithm, it combines the Gauss–Newton algorithm with gradient descent, but it uses an explicit trust ...

  7. Total least squares - Wikipedia

    en.wikipedia.org/wiki/Total_least_squares

    where [] is the augmented matrix with E and F side by side and ‖ ‖ is the Frobenius norm, the square root of the sum of the squares of all entries in a matrix and so equivalently the square root of the sum of squares of the lengths of the rows or columns of the matrix. This can be rewritten as

  8. Linear multistep method - Wikipedia

    en.wikipedia.org/wiki/Linear_multistep_method

    Linear multistep methods are used for the numerical solution of ordinary differential equations. Conceptually, a numerical method starts from an initial point and then takes a short step forward in time to find the next solution point. The process continues with subsequent steps to map out the solution.

  9. Euler method - Wikipedia

    en.wikipedia.org/wiki/Euler_method

    For this reason, the Euler method is said to be a first-order method, while the midpoint method is second order. We can extrapolate from the above table that the step size needed to get an answer that is correct to three decimal places is approximately 0.00001, meaning that we need 400,000 steps.