This volume treats linear regression diagnostics as a tool for the
application of linear regression models to real-life data. The
presentation makes extensive use of examples to illustrate theory.
The text assesses the effect of measurement errors on the estimated
coefficients, which is not accounted for in a standard least
squares estimate, but is important where regression coefficients
are used to apportion effects due to different variables. The
robustness of the regression fit is assessed qualitatively and
numerically.
General
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