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  2. 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 ...

  3. XLfit - Wikipedia

    en.wikipedia.org/wiki/XLfit

    XLfit is a Microsoft Excel add-in that can perform regression analysis, curve fitting, and statistical analysis. It is approved by the UK National Physical Laboratory and the US National Institute of Standards and Technology [1] XLfit can generate 2D and 3D graphs and analyze data sets. XLfit can also analyse the statistical data.

  4. List of statistical software - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_software

    Simfit – simulation, curve fitting, statistics, and plotting; SOCR; SOFA Statistics – desktop GUI program focused on ease of use, learn as you go, and beautiful output; Stan (software) – open-source package for obtaining Bayesian inference using the No-U-Turn sampler, a variant of Hamiltonian Monte Carlo. It is somewhat like BUGS, but ...

  5. 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.

  6. Polynomial regression - Wikipedia

    en.wikipedia.org/wiki/Polynomial_regression

    For example, x and x 2 have ... Microsoft Excel makes use of polynomial regression when fitting a trendline to data points on an X Y scatter plot. ... Curve Fitting, ...

  7. Nonlinear regression - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_regression

    The best-fit curve is often assumed to be that which minimizes the sum of squared residuals. This is the ordinary least squares (OLS) approach. However, in cases where the dependent variable does not have constant variance, or there are some outliers, a sum of weighted squared residuals may be minimized; see weighted least squares.

  8. Stretched exponential function - Wikipedia

    en.wikipedia.org/wiki/Stretched_exponential_function

    The curves converge to a Dirac delta function peaked at u = 1 as β approaches 1, corresponding to the simple exponential function. Figure 2 . Linear and log-log plots of the stretched exponential distribution function G {\displaystyle G} vs t / τ {\displaystyle t/\tau }

  9. Probability distribution fitting - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution...

    Probability distribution fitting or simply distribution fitting is the fitting of a probability distribution to a series of data concerning the repeated measurement of a variable phenomenon. The aim of distribution fitting is to predict the probability or to forecast the frequency of occurrence of the magnitude of the phenomenon in a certain ...