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  2. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    The residual is the difference between the observed value and the estimated value of the quantity of interest (for example, a sample mean). The distinction is most important in regression analysis , where the concepts are sometimes called the regression errors and regression residuals and where they lead to the concept of studentized residuals .

  3. Iteratively reweighted least squares - Wikipedia

    en.wikipedia.org/wiki/Iteratively_reweighted...

    IRLS can be used for ℓ 1 minimization and smoothed ℓ p minimization, p < 1, in compressed sensing problems. It has been proved that the algorithm has a linear rate of convergence for ℓ 1 norm and superlinear for ℓ t with t < 1, under the restricted isometry property, which is generally a sufficient condition for sparse solutions.

  4. Linear least squares - Wikipedia

    en.wikipedia.org/wiki/Linear_least_squares

    Linear Template Fit (LTF) [7] combines a linear regression with (generalized) least squares in order to determine the best estimator. The Linear Template Fit addresses the frequent issue, when the residuals cannot be expressed analytically or are too time consuming to be evaluate repeatedly, as it is often the case in iterative minimization ...

  5. Minimal residual method - Wikipedia

    en.wikipedia.org/wiki/Minimal_residual_method

    The matrix used comes from a 2D boundary-value problem. The Minimal Residual Method or MINRES is a Krylov subspace method for the iterative solution of symmetric linear equation systems . It was proposed by mathematicians Christopher Conway Paige and Michael Alan Saunders in 1975.

  6. Residual (numerical analysis) - Wikipedia

    en.wikipedia.org/wiki/Residual_(numerical_analysis)

    When one does not know the exact solution, one may look for the approximation with small residual. Residuals appear in many areas in mathematics, including iterative solvers such as the generalized minimal residual method , which seeks solutions to equations by systematically minimizing the residual.

  7. Microsoft Math Solver - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Math_Solver

    Microsoft Math contains features that are designed to assist in solving mathematics, science, and tech-related problems, as well as to educate the user. The application features such tools as a graphing calculator and a unit converter. It also includes a triangle solver and an equation solver that provides step-by-step solutions to each problem.

  8. Levenberg–Marquardt algorithm - Wikipedia

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

    The choice of the finite difference step can affect the stability of the algorithm, and a value of around 0.1 is usually reasonable in general. [ 8 ] Since the acceleration may point in opposite direction to the velocity, to prevent it to stall the method in case the damping is too small, an additional criterion on the acceleration is added in ...

  9. Template:Math templates - Wikipedia

    en.wikipedia.org/wiki/Template:Math_templates

    {{Math templates | state = collapsed}} will show the template collapsed, i.e. hidden apart from its title bar. {{ Math templates | state = autocollapse }} will show the template autocollapsed, i.e. if there is another collapsible item on the page (a navbox, sidebar , or table with the collapsible attribute ), it is hidden apart from its title ...