estimated regression
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Regression dilution — is a statistical phenomenon also known as attenuation . Consider fitting a straight line for the relationship of an outcome variable y to a predictor variable x, and estimating the gradient (slope) of the line. Statistical variability,… … Wikipedia
Regression analysis — In statistics, regression analysis is a collective name for techniques for the modeling and analysis of numerical data consisting of values of a dependent variable (response variable) and of one or more independent variables (explanatory… … Wikipedia
Regression toward the mean — In statistics, regression toward the mean (also known as regression to the mean) is the phenomenon that if a variable is extreme on its first measurement, it will tend to be closer to the average on a second measurement, and a fact that may… … Wikipedia
Regression discontinuity design — In statistics, econometrics, epidemiology and related disciplines, a regression discontinuity design (RDD) is a design that elicits the causal effects of interventions by exploiting a given exogenous threshold determining assignment to treatment … Wikipedia
Regression model validation — In statistics, model validation is possibly the most important step in the model building sequence. It is also one of the most overlooked.[citation needed] Often the validation of a model seems to consist of nothing more than quoting the R2… … 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
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
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
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
Nonlinear regression — See Michaelis Menten kinetics for details 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… … Wikipedia
Quantile regression — is a type of regression analysis used in statistics. Whereas the method of least squares results in estimates that approximate the conditional mean of the response variable given certain values of the predictor variables, quantile regression… … Wikipedia
