… In this book we assume that the underlying model is a linear regression model (with or
without intercept). Nonetheless, every statement will be true under any type of model which …

… general linear model. Because the neglect of correlation between regression disturbances
… autocorrelation in the context of the linear regression model. This particular testing problem …

… in multiple versus simple linear regression is that the multiple regression model includes the
… This is analogous to the simple linear regression model in which the slope of the regression …

… LINEAR REGRESSION The null hypothesis for all tests is the standard linear regression
model… of tests for spatial dependence in regression models. The most important finding is the …

… Furthermore, hypothesis tests from linear regression models using arbitrary-transformed
outcomes are still valid. However, when using linear regression models, we assume …

… linear regression model can be used for all kinds of LR functional data and in particular for
interval-grouped data. The linear regression model … sets, or considering nonlinear regression. …

… displays for regression analysis that characterize the overall nature of the regression model,
… theory and empirical findings in the specification, testing, and revision of regression models. …

… To do so, we used a real data set and estimated two prespecified linear regression models
using ordinary least squares. Subsets of increasing size were then randomly drawn from the …

… using a linear regression model to predict Y from the X’s. The regression model makes very
… effects of the X’s with respect to Y are linear and additive and non-interactive and that any …

… variable in a linear regression model is not … regression models that allow for spatially
varying coefficients. Two competing models of this type are geographically weighted regression …