In robust statistics, robust regression seeks to overcome some limitations of traditional regression analysis. A regression analysis models the relationship...

Theil–Sen estimator is a method for robustly fitting a line to sample points in the plane (simple linear regression) by choosing the median of the slopes...

Local regression or local polynomial regression, also known as moving regression, is a generalization of the moving average and polynomial regression. Its...

Look up regression, regressions, or régression in Wiktionary, the free dictionary. Regression or regressions may refer to: Marine regression, coastal advance...

inefficiencies of the initial estimator. Robust confidence intervals Robust regression Unit-weighted regression Sarkar, Palash (2014-05-01). "On some connections...

In statistics, the Huber loss is a loss function used in robust regression, that is less sensitive to outliers in data than the squared error loss. A...

called regressors, predictors, covariates, explanatory variables or features). The most common form of regression analysis is linear regression, in which...

the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables...

maximum likelihood estimates of a generalized linear model, and in robust regression to find an M-estimator, as a way of mitigating the influence of outliers...

Median absolute deviation Ordinary least squares Robust regression "Least Absolute Deviation Regression". The Concise Encyclopedia of Statistics. Springer...