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  2. Segmented regression - Wikipedia

    en.wikipedia.org/wiki/Segmented_regression

    Segmented regression, also known as piecewise regression or broken-stick regression, is a method in regression analysis in which the independent variable is partitioned into intervals and a separate line segment is fit to each interval. Segmented regression analysis can also be performed on multivariate data by partitioning the various ...

  3. SegReg - Wikipedia

    en.wikipedia.org/wiki/SegReg

    In statistics and data analysis, the application software SegReg is a free and user-friendly tool for linear segmented regression analysis to determine the breakpoint where the relation between the dependent variable and the independent variable changes abruptly.

  4. Piecewise linear function - Wikipedia

    en.wikipedia.org/wiki/Piecewise_linear_function

    In mathematics, a piecewise linear or segmented function is a real-valued function of a real variable, whose graph is composed of straight-line segments. [ 1 ] Definition

  5. 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 ...

  6. Template:Least squares and regression analysis - Wikipedia

    en.wikipedia.org/wiki/Template:Least_squares_and...

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Help; Learn to edit; Community portal; Recent changes; Upload file

  7. Regression discontinuity design - Wikipedia

    en.wikipedia.org/wiki/Regression_discontinuity...

    Note that regression kinks (or kinked regression) can also mean a type of segmented regression, which is a different type of analysis. Final considerations. The RD design takes the shape of a quasi-experimental research design with a clear structure that is devoid of randomized experimental features.

  8. 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 ...

  9. Multivariate adaptive regression spline - Wikipedia

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

    Thus, for example, MARS models can incorporate logistic regression to predict probabilities. Non-linear regression is used when the underlying form of the function is known and regression is used only to estimate the parameters of that function. MARS, on the other hand, estimates the functions themselves, albeit with severe constraints on the ...