TY - JOUR
T1 - Diagnostic procedures
AU - McKean, Joseph W.
AU - Sheather, Simon J.
PY - 2009
Y1 - 2009
N2 - Diagnostic procedures are used to check the quality of a fit of a model, to verify the validity of the assumptions behind the model, and to find outlying and/or highly influential observations. Our discussion focuses on the linear model (the most widely used model). Much of our discussion, however, pertains to other models, as we show when we extend our discussion to mixed models at the end of the paper. The traditional fit, least squares (LS), can be severely impaired by just one outlier. So along with LS we present two robust fits and diagnostic procedures which explore the differences among the three fits. These comparisons generally find the outlying and influential cases. Armed with this methodology, we then proceed to discuss diagnostics that explore the quality of fit and verify the validity of the assumptions, including independent and identically distributed errors and normality.
AB - Diagnostic procedures are used to check the quality of a fit of a model, to verify the validity of the assumptions behind the model, and to find outlying and/or highly influential observations. Our discussion focuses on the linear model (the most widely used model). Much of our discussion, however, pertains to other models, as we show when we extend our discussion to mixed models at the end of the paper. The traditional fit, least squares (LS), can be severely impaired by just one outlier. So along with LS we present two robust fits and diagnostic procedures which explore the differences among the three fits. These comparisons generally find the outlying and influential cases. Armed with this methodology, we then proceed to discuss diagnostics that explore the quality of fit and verify the validity of the assumptions, including independent and identically distributed errors and normality.
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U2 - 10.1002/wics.12
DO - 10.1002/wics.12
M3 - Article
AN - SCOPUS:78651561171
SN - 1939-5108
VL - 1
SP - 221
EP - 233
JO - Wiley Interdisciplinary Reviews: Computational Statistics
JF - Wiley Interdisciplinary Reviews: Computational Statistics
IS - 2
ER -