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  2. Levenberg–Marquardt algorithm - Wikipedia

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

    In mathematics and computing, the Levenberg–Marquardt algorithm (LMA or just LM), also known as the damped least-squares (DLS) method, is used to solve non-linear least squares problems. These minimization problems arise especially in least squares curve fitting. The LMA interpolates between the Gauss–Newton algorithm (GNA) and the method ...

  3. Ramer–Douglas–Peucker algorithm - Wikipedia

    en.wikipedia.org/wiki/Ramer–Douglas–Peucker...

    Ramer–Douglas–Peucker algorithm. The Ramer–Douglas–Peucker algorithm, also known as the Douglas–Peucker algorithm and iterative end-point fit algorithm, is an algorithm that decimates a curve composed of line segments to a similar curve with fewer points. It was one of the earliest successful algorithms developed for cartographic ...

  4. Non-linear least squares - Wikipedia

    en.wikipedia.org/wiki/Non-linear_least_squares

    v. t. e. Non-linear least squares is the form of least squares analysis used to fit a set of m observations with a model that is non-linear in n unknown parameters (m ≥ n). It is used in some forms of nonlinear regression. The basis of the method is to approximate the model by a linear one and to refine the parameters by successive iterations.

  5. 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 ...

  6. Gauss–Newton algorithm - Wikipedia

    en.wikipedia.org/wiki/Gauss–Newton_algorithm

    The Gauss–Newton algorithm is used to solve non-linear least squares problems, which is equivalent to minimizing a sum of squared function values. It is an extension of Newton's method for finding a minimum of a non-linear function. Since a sum of squares must be nonnegative, the algorithm can be viewed as using Newton's method to iteratively ...

  7. Fityk - Wikipedia

    en.wikipedia.org/wiki/Fityk

    Fityk. Fityk is curve fitting and data analysis application, predominantly used to fit analytical, bell-shaped functions to experimental data. It is positioned to fill the gap between general plotting software and programs specific for one field, e.g. crystallography or XPS. [1] Originally, Fityk was developed to analyse powder diffraction data.

  8. SciDAVis - Wikipedia

    en.wikipedia.org/wiki/SciDAVis

    Curve fitting can be performed with user-defined or built-in linear and nonlinear functions, including multi-peak fitting, based on the GNU Scientific Library. The plots can be exported to several bitmap formats, PDF, EPS or SVG. Note windows support in-place evaluation of mathematical expressions or an optional scripting interface to Python.

  9. Smoothing - Wikipedia

    en.wikipedia.org/wiki/Smoothing

    Smoothing. In statistics and image processing, to smooth a data set is to create an approximating function that attempts to capture important patterns in the data, while leaving out noise or other fine-scale structures/rapid phenomena. In smoothing, the data points of a signal are modified so individual points higher than the adjacent points ...