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  2. Least squares - Wikipedia

    en.wikipedia.org/wiki/Least_squares

    The result of fitting a set of data points with a quadratic function Conic fitting a set of points using least-squares approximation. In regression analysis, least squares is a parameter estimation method based on minimizing the sum of the squares of the residuals (a residual being the difference between an observed value and the fitted value provided by a model) made in the results of each ...

  3. Line fitting - Wikipedia

    en.wikipedia.org/wiki/Line_fitting

    Line fitting is the process of constructing a straight line that has the best fit to a series of data points. Several methods exist, considering: Vertical distance: Simple linear regression; Resistance to outliers: Robust simple linear regression

  4. Curve fitting - Wikipedia

    en.wikipedia.org/wiki/Curve_fitting

    Curve fitting [1] [2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints. [ 4 ] [ 5 ] Curve fitting can involve either interpolation , [ 6 ] [ 7 ] where an exact fit to the data is required, or smoothing , [ 8 ] [ 9 ] in which a "smooth ...

  5. Symbolab - Wikipedia

    en.wikipedia.org/wiki/Symbolab

    Symbolab is an answer engine [1] that provides step-by-step solutions to mathematical problems in a range of subjects. [2] It was originally developed by Israeli start-up company EqsQuest Ltd., under whom it was released for public use in 2011. In 2020, the company was acquired by American educational technology website Course Hero. [3] [4]

  6. Goodness of fit - Wikipedia

    en.wikipedia.org/wiki/Goodness_of_fit

    The goodness of fit of a statistical model describes how well it fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between ...

  7. Levenberg–Marquardt algorithm - Wikipedia

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

    In this example we try to fit the function = ⁡ + ⁡ using the Levenberg–Marquardt algorithm implemented in GNU Octave as the leasqr function. The graphs show progressively better fitting for the parameters a = 100 {\displaystyle a=100} , b = 102 {\displaystyle b=102} used in the initial curve.

  8. Piecewise linear function - Wikipedia

    en.wikipedia.org/wiki/Piecewise_linear_function

    The graph is made using the method of least squares to find the two segments with the best fit. The graph on the right reveals that crop yields tolerate a soil salinity up to ECe = 8 dS/m (ECe is the electric conductivity of an extract of a saturated soil sample), while beyond that value the crop production reduces. The graph is made with the ...

  9. Linear approximation - Wikipedia

    en.wikipedia.org/wiki/Linear_approximation

    Linear approximation is a method of estimating the value of a function near a given point using the tangent line at that point.