Abstract
In the above, we have assumed several things: (i) the mean μ = Ey is a linear function of the regressors, or of the parameters; (ii) the errors are additive; (iii) the errors are independent; (iv) the errors are normally distributed (Gaussian); (v) the errors have equal variance.
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RⓇ: A language and environment for statistical computing. © 2009 R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0 http://www.R-project.org
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Bingham, N.H., Fry, J.M. (2010). Model Checking and Transformation of Data. In: Regression. Springer Undergraduate Mathematics Series. Springer, London. https://doi.org/10.1007/978-1-84882-969-5_7
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DOI: https://doi.org/10.1007/978-1-84882-969-5_7
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