Now that you've got a good sense of how to 'speak' R, let's use it with linear regression to make distinctive predictions.

I predict you'll find this logistic regression example with R to be helpful for gleaning useful information from common binary classification problems.

To do this in R we must first make sure we limit our data frame to numerical variables (the regression function creates dummies automatically, but AirEntrain remains a categorical variable). To do ...

We provide a remedy for two concerns that have dogged the use of principal components in regression: (i) principal components are computed from the predictors alone and do not make apparent use of the ...

A comparison between parametric and nonparametric regression in terms of fitting and prediction criteria. Methods of fitting semi/nonparametric regression models.

Regression analysis is a quantitative tool that is easy to use and can provide valuable information on financial analysis and forecasting.

Regression is a vital tool for estimating investing outcomes based on various inputs. Regression is a vital tool for predicting outcomes in investing and other pursuits. Find out what it means ...

Ying Wei, Raymond J. Carroll, Quantile Regression With Measurement Error, Journal of the American Statistical Association, Vol. 104, No. 487 (September 2009), pp. 1129-1143 ...