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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. Nonlinear autoregressive exogenous model - Wikipedia

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

    In time series modeling, a nonlinear autoregressive exogenous model (NARX) is a nonlinear autoregressive model which has exogenous inputs. This means that the model relates the current value of a time series to both: past values of the same series; and

  4. 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.

  5. Non-linear mixed-effects modeling software - Wikipedia

    en.wikipedia.org/wiki/Non-linear_mixed-effects...

    Nonlinear mixed-effects models are a special case of regression analysis for which a range of different software solutions are available. The statistical properties of nonlinear mixed-effects models make direct estimation by a BLUE estimator impossible. Nonlinear mixed effects models are therefore estimated according to Maximum Likelihood ...

  6. Seemingly unrelated regressions - Wikipedia

    en.wikipedia.org/.../Seemingly_unrelated_regressions

    In econometrics, the seemingly unrelated regressions (SUR) [1]: 306 [2]: 279 [3]: 332 or seemingly unrelated regression equations (SURE) [4] [5]: 2 model, proposed by Arnold Zellner in (1962), is a generalization of a linear regression model that consists of several regression equations, each having its own dependent variable and potentially ...

  7. Multivariate adaptive regression spline - Wikipedia

    en.wikipedia.org/wiki/Multivariate_adaptive...

    In statistics, multivariate adaptive regression splines (MARS) is a form of regression analysis introduced by Jerome H. Friedman in 1991. [1] It is a non-parametric regression technique and can be seen as an extension of linear models that automatically models nonlinearities and interactions between variables.

  8. Nonlinear mixed-effects model - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_mixed-effects_model

    Nonlinear mixed-effects models constitute a class of statistical models generalizing linear mixed-effects models. Like linear mixed-effects models, they are particularly useful in settings where there are multiple measurements within the same statistical units or when there are dependencies between measurements on related statistical units.

  9. Nonlinear modelling - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_modelling

    Nonlinear modelling in practice therefore means modelling of phenomena in which independent variables affecting the system can show complex and synergetic nonlinear effects. Contrary to traditional modelling methods, such as linear regression and basic statistical methods, nonlinear modelling can be utilized efficiently in a vast number of ...