Flexible modelling using basis expansions (Chapter 5) Linear ...

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Example: heart dataThe individual coefficients don’t mean anything, we need toevaluate groups of coefficients. We can do this with successivelikelihood ratio tests, by hand, e.g.> summary(glm(chd˜ns.sbp+ns.ldl+famhist+ns.obesity+ns.alcohol+ns.age,+ family=binomial, data=hr)) # I left out tobacco... stuff omittedNull deviance: 596.11 on 461 degrees of freedomResidual deviance: 469.61 on 440 degrees of freedomAIC: 513.61Number of Fisher Scoring iterations: 5> 469.61-457.63[1] 11.98> pchisq(11.98,4)[1] 0.9824994> 1-.Last.value[1] 0.01750061 # doesn’t agree exactly with the book, but closeSee Figure 5.4: , 8
Example: heart dataThe function stepAIC does all this for you:> ns.hr.step #> # Here we are at Table 5.1; note that alcohol has been dropped from the> # model: , 9
Page 1 and 2: STA 450/4000 S: February 2 2005Flex
Page 4 and 5: Regression splines◮ Constraints o
Page 6 and 7: Regression splines◮ The B-spline
Page 10 and 11: The function stepAIC does all this
Page 12 and 13: Smoothing splines◮ How many param
Page 14: Smoothing splinesA smoothing spline

Flexible modelling using basis expansions (Chapter 5) Linear ...

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