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  2. Nonlinear regression - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_regression

    In statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or more independent variables. The data are fitted by a method of successive approximations (iterations).

  3. Non-linear least squares - Wikipedia

    en.wikipedia.org/wiki/Non-linear_least_squares

    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.

  4. 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 ...

  5. Nonlinear mixed-effects model - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_mixed-effects_model

    A popular approach is the Lindstrom-Bates algorithm [3] which relies on iteratively optimizing a nonlinear problem, locally linearizing the model around this optimum and then employing conventional methods from linear mixed-effects models to do maximum likelihood estimation.

  6. Gauss–Newton algorithm - Wikipedia

    en.wikipedia.org/wiki/Gauss–Newton_algorithm

    In this example, the Gauss–Newton algorithm will be used to fit a model to some data by minimizing the sum of squares of errors between the data and model's predictions. In a biology experiment studying the relation between substrate concentration [S] and reaction rate in an enzyme-mediated reaction, the data in the following table were obtained.

  7. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    For example, a simple univariate regression may propose (,) = +, suggesting that the researcher believes = + + to be a reasonable approximation for the statistical process generating the data. Once researchers determine their preferred statistical model , different forms of regression analysis provide tools to estimate the parameters β ...

  8. Are these prices a mistake? Someone forgot to turn off these ...

    www.aol.com/lifestyle/are-these-prices-a-mistake...

    We've been keeping tabs on this practical storage cart for a while, and now the black version is $10 cheaper than it was on Black Friday! This rolling storage island is like adding three extra ...

  9. Nonlinear autoregressive exogenous model - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_autoregressive...

    For example, y may be air temperature at noon, and u may be the day of the year (day-number within year). The function F is some nonlinear function, such as a polynomial. F can be a neural network, a wavelet network, a sigmoid network and so on.