Preface to First Edition - lib

SUMMARY 115R> plot(clouds_lm)Cook's distance2Cook's distance0 2 4 6 81185 10 15 20Obs. numberlm(clouds_formula)Figure 6.9Index plot of Cook’s distances for cloud seeding data.diagnostic plots similar to those mentioned in the text. (The elements ofthe hat matrix can be obtained from the lm.influence function.)Ex. 6.2 Investigate refitting the cloud seeding data after removing any observationswhich may give cause for concern.Ex. 6.3 Show how the analysis of variance table for the data in Table 5.1of the previous chapter can be constructed from the results of applying anappropriate multiple linear regression to the data.Ex. 6.4 Investigate the use of the leaps function from package leaps (Lumleyand Miller, 2009) for selecting the ‘best’ set of variables predicting rainfallin the cloud seeding data.© 2010 by Taylor and Francis Group, LLC