• Nonparametric regression is a form of regression analysis where the predictor does not take a predetermined form but is completely constructed using information...
    7 KB (677 words) - 05:52, 7 July 2025
  • non-linear relation between a pair of random variables X and Y. In any nonparametric regression, the conditional expectation of a variable Y {\displaystyle Y}...
    9 KB (1,261 words) - 07:54, 4 June 2024
  • Linear equation Logistic regression M-estimator Multivariate adaptive regression spline Nonlinear regression Nonparametric regression Normal equations Projection...
    76 KB (10,482 words) - 04:54, 7 July 2025
  • Thumbnail for Regression analysis
    models (e.g., nonparametric regression). Regression analysis is primarily used for two conceptually distinct purposes. First, regression analysis is widely...
    37 KB (5,235 words) - 03:23, 20 June 2025
  • Thumbnail for Isotonic regression
    In statistics and numerical analysis, isotonic regression or monotonic regression is the technique of fitting a free-form line to a sequence of observations...
    10 KB (1,449 words) - 20:24, 19 June 2025
  • method to estimate a probability distribution. Nonparametric regression and semiparametric regression methods have been developed based on kernels, splines...
    13 KB (1,692 words) - 00:24, 20 June 2025
  • Thumbnail for Local regression
    Local regression or local polynomial regression, also known as moving regression, is a generalization of the moving average and polynomial regression. Its...
    34 KB (5,833 words) - 07:26, 12 July 2025
  • "multilevel regression" and "poststratification" ideas of MRP can be generalized. Multilevel regression can be replaced by nonparametric regression or regularized...
    14 KB (1,648 words) - 23:28, 24 June 2025
  • In statistics, semiparametric regression includes regression models that combine parametric and nonparametric models. They are often used in situations...
    7 KB (1,170 words) - 02:39, 7 May 2022
  • represents an improved technique in the neural networks based on the nonparametric regression. The idea is that every training sample will represent a mean to...
    3 KB (461 words) - 06:00, 24 April 2025
  • Thumbnail for Polynomial regression
    In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable...
    15 KB (2,406 words) - 23:39, 31 May 2025
  • Thumbnail for Mathematical statistics
    data (e.g. using ordinary least squares). Nonparametric regression refers to techniques that allow the regression function to lie in a specified set of functions...
    17 KB (1,935 words) - 07:44, 30 December 2024
  • adaptive regression splines (MARS) is a form of regression analysis introduced by Jerome H. Friedman in 1991. It is a non-parametric regression technique...
    18 KB (2,701 words) - 04:09, 11 July 2025
  • Least absolute deviations Model selection Nonparametric regression Tikhonov regularization "What is lasso regression?". ibm.com. 18 January 2024. Retrieved...
    52 KB (8,057 words) - 00:46, 6 July 2025
  • doi:10.1007/978-0-387-84858-7, [1] (eq.(5.16)) Fox, J. (2000). Nonparametric Simple Regression: Smoothing Scatterplots. Quantitative Applications in the Social...
    30 KB (4,530 words) - 12:18, 18 June 2025
  • Additive model (category Nonparametric regression)
    In statistics, an additive model (AM) is a nonparametric regression method. It was suggested by Jerome H. Friedman and Werner Stuetzle (1981) and is an...
    3 KB (424 words) - 04:09, 31 December 2024
  • Kernel (statistics) (category Nonparametric statistics)
    classification, regression analysis, and cluster analysis on data in an implicit space. This usage is particularly common in machine learning. In nonparametric statistics...
    12 KB (899 words) - 20:19, 3 April 2025
  • Alternating conditional expectations (category Nonparametric regression)
    statistics, Alternating Conditional Expectations (ACE) is a nonparametric algorithm used in regression analysis to find the optimal transformations for both...
    7 KB (1,203 words) - 01:25, 27 April 2025
  • Linear regression Simple linear regression Logistic regression Nonlinear regression Nonparametric regression Robust regression Stepwise regression Regression...
    2 KB (241 words) - 02:53, 1 December 2024
  • from the conventional linear model. Developments towards fully nonparametric regression models for functional data encounter problems such as curse of...
    48 KB (6,704 words) - 20:31, 18 July 2025
  • Generalized additive model (category Nonparametric regression)
    specified parametric form (for example a polynomial, or an un-penalized regression spline of a variable) or may be specified non-parametrically, or semi-parametrically...
    39 KB (5,716 words) - 03:59, 9 May 2025
  • Ridge regression (also known as Tikhonov regularization, named for Andrey Tikhonov) is a method of estimating the coefficients of multiple-regression models...
    31 KB (4,148 words) - 18:20, 3 July 2025
  • Thumbnail for Kriging
    linear statistics Gaussian process Multivariate interpolation Nonparametric regression Radial basis function interpolation Space mapping Spatial dependence...
    39 KB (6,063 words) - 23:47, 20 May 2025
  • Thumbnail for Logistic regression
    combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) estimates the parameters of a logistic model...
    121 KB (19,414 words) - 03:19, 24 July 2025
  • Passing–Bablok regression is a method from robust statistics for nonparametric regression analysis suitable for method comparison studies introduced by...
    6 KB (759 words) - 18:51, 13 January 2024
  • Thumbnail for Quantile regression
    Quantile regression is a type of regression analysis used in statistics and econometrics. Whereas the method of least squares estimates the conditional...
    30 KB (4,259 words) - 22:29, 17 July 2025
  • nearest neighbor. The k-NN algorithm can also be generalized for regression. In k-NN regression, also known as nearest neighbor smoothing, the output is the...
    32 KB (4,333 words) - 23:48, 16 April 2025
  • quantile and nonparametric estimators have also been developed. These and other censored regression models are often confused with truncated regression models...
    3 KB (355 words) - 14:45, 4 March 2025
  • Thumbnail for Ordinary least squares
    especially in the case of a simple linear regression, in which there is a single regressor on the right side of the regression equation. The OLS estimator is consistent...
    65 KB (9,098 words) - 10:14, 3 June 2025
  • Boor's official site [1]. Green, P. J.; Silverman, B.W. (1994). Nonparametric Regression and Generalized Linear Models: A roughness penalty approach. Chapman...
    14 KB (2,314 words) - 09:45, 13 May 2025