Residuals and Influence in Regression

Conlputat ions E.ratnple 2.3.4Jer Jiyhters no.I 2.3.3Partial residual plots Esantple 2.3.5 Jef fiyhrers no. 2 2.3.4Probability plots E.ratrtpIe 2.3.6 Cloud seeditty no. 4 2.4 Transformations 2.4.1 Fanlilies of fratlsjorr~ratiot~s 2.4.2Selectb~g a trat~s/'orrtlatiott Itr~.ariattceNor~rrality Choice c?/'trtodel i ~t t c i scalirlg the predictors It~f'erettce E.uan~ple 2.4.1 Tree data 110.I 2.4.3Diagnostic ntetttods A tkinson 's method Andrew' nterhod Application to the power family Tukey's test E.rample 2.4.2Tree data no. 2 E.~antple 2.4.3Jet fiyhters no. 3 2.4.4Trarrsfor~r~ing the esplana~ory ~lariahles Esatrtple 2.4.4Tree data no. 3 Esatrtple 2.4.5 Cloud see(fittg no. 5 2.5 Residual analysis in two-way tables 2.5.1 Otitliers 2.5.2Nottaciditirity E.\-antple 2.5.1 A y ricultural e-rperintenl 3 Assessment of influence 3.1 Motivation 3.2 The influence curve E.uatrtple 3.2.1The sanlple auerage3.3 The influence curve in the linear model 3.4 Sample versions of the influence curve 3.4.1 E~rtpiricnl ittfl~iet~i-e curves 3.4.2Sotrtple it~fltrettce curres Esntilple 3.4.1 C l o ~i d seeding tlo.6 E.uittr~ple 3.4.2Partial Ffesrs 3.5 Applications of the sample influence curve 3.5.1 Estert~al scalit~g bI = XTX, c = p'62 Euatrtple 3.5.1 C'omhinafion.sqf r f , vii Esanlple 3.5.2Rat data Alrernatice full rank choices for M, c Lower dintensior~al trortrts E.ratiiple 3.5.3Cloud seeding 110.7