… problems where a linear predictor can only be … linear predictor is accurate on a conditional
distribution described by some simple condition. Note that neither the condition nor the linear …

… a linear rule a giving conditional expected error ǫ (and c is true with probability µ), we find a
condition c′ and a linear rule a′ with conditional … for the dense regression and expected-…

… we advocate a general linear model approach to assessing … The approach consists of
comparing a series of linear regression … Hopefully we have made quite clear that linear regression …

… Many operative extensions of linear regression models have … The following linear regression
model is called the global … The following linear regression model defines the first auxiliary …

… In correctly specified linear regression, the expected generalization error does not depend
… However, in misspecified linear regression which we discuss in this paper, the expected …

… approach to the statistical analysis of linear and nonlinear response models, but it cannot deal
… the mean regression, therefore, they cannot be used to characterize the entire conditional …

… Chapter 2 provides a quick but thorough presentation of simple linear regression. Topics …
simple linear regression equation, explanation of the ordinary least squares regression criteria, …

… The properties of Stein-type estimators for the linear regression … The shrinkage estimation
for the ill conditioned model is … [37] estimators for the ill conditioned linear regression model. …

… of a dependent variable in a simple linear regression model when it is suspected that the …
of estimation of a conditional mean of a dependent variable in the first regression model by …

… marginal conditional quantiles of multivariate response variables in a linear regression …
and the well-known univariate quantile regression model to a multivariate context, ie, when …