search for: dev_x2

...ple adapted from the previous post from Simon Wood. I guess so... ## fit full and reduced models... b <- gam(y~offset(x)+s(x1)+s(x2)) b1 <- gam(y~offset(x)+s(x1),sp=b$sp[ 1]) b2 <- gam(y~offset(x)+s(x2),sp=b$sp[2]) b0 <- gam(y~offset(x)+1) ## calculate proportions deviance explained... dev_x2 <-(deviance(b1)-deviance(b))/deviance(b0) ## prop explained by s(x2) dev_x1 <-(deviance(b2)-deviance(b))/deviance(b0) ## prop explained by s(x1) for example, if dev_x2 = 0.4 and dev_x1 =0.1, is the remaining 0.5 corresponds to the proportion of variance explained by the interaction between t...