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non-parametric regression

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  • Non-parametric statistics — In statistics, the term non parametric statistics has at least two different meanings: The first meaning of non parametric covers techniques that do not rely on data belonging to any particular distribution. These include, among others:… …   Wikipedia

  • Nonparametric regression — is a form of regression analysis in which the predictor does not take a predetermined form but is constructed according to information derived from the data. Nonparametric regression requires larger sample sizes than regression based on… …   Wikipedia

  • Multivariate adaptive regression splines — (MARS) is a form of regression analysis introduced by Jerome Friedman in 1991.[1] It is a non parametric regression technique and can be seen as an extension of linear models that automatically models non linearities and interactions. The term… …   Wikipedia

  • Isotonic regression — In numerical analysis, isotonic regression (IR) involves finding a weighted least squares fit to a vector with weights vector subject to a set of monotonicity constraints giving a simple or partial order over the variables. The monotonicity… …   Wikipedia

  • Robust regression — In robust statistics, robust regression is a form of regression analysis designed to circumvent some limitations of traditional parametric and non parametric methods. Regression analysis seeks to find the effect of one or more independent… …   Wikipedia

  • Linear regression — Example of simple linear regression, which has one independent variable In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. The case of one… …   Wikipedia

  • Kernel regression — Not to be confused with Kernel principal component analysis. The kernel regression is a non parametric technique in statistics to estimate the conditional expectation of a random variable. The objective is to find a non linear relation between a… …   Wikipedia

  • Bayesian additive regression kernels — (BARK) is a non parametric statistics model for regression and classificationcite web| title= Bayesian Additive Regression Kernels |url= http://stat.duke.edu/people/theses/OuyangZ.html |Author = Zhi Ouyang |Publisher = Duke University] . The… …   Wikipedia

  • Local regression — LOESS, or locally weighted scatterplot smoothing, is one of many modern modeling methods that build on classical methods, such as linear and nonlinear least squares regression. Modern regression methods are designed to address situations in which …   Wikipedia

  • Degrees of freedom (statistics) — In statistics, the number of degrees of freedom is the number of values in the final calculation of a statistic that are free to vary.[1] Estimates of statistical parameters can be based upon different amounts of information or data. The number… …   Wikipedia

  • Errors-in-variables models — In statistics and econometrics, errors in variables models or measurement errors models are regression models that account for measurement errors in the independent variables. In contrast, standard regression models assume that those regressors… …   Wikipedia

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