问有没有办法产生不居中的predict.gam(...，type="terms")值？

EN

    # read in data
    air<-data.frame(airquality)
    air<-air[complete.cases(air),]

    # set up m odel
    model<-gam(Temp~s(Ozone) + s(Solar.R) + s(Wind),data=air,method="ML")

#get predicted values 
predicted<-as.data.frame(predict(model,na.action=na.exclude))

    colnames(predicted)<-"predicted"

# using the lpmatrix, set values of s(Ozone), s(Solar.R), and s(Wind) to 0    
lpmat<-predict(model, type="lpmatrix")
    lpmat_Ozone<-lpmat; lpmat_Ozone[,grep("Ozone",colnames(lpmat))]<-0
    lpmat_Solar.R<-lpmat; lpmat_Solar.R[,grep("Solar.R",colnames(lpmat))]<-0
    lpmat_Wind<-lpmat; lpmat_Wind[,grep("Wind",colnames(lpmat))]<-0

#obtain response predictions with s(each variable) set to 0 (respectively)
    predicted$Ozone<-unname(lpmat_Ozone%*%coef(model))[,1]
    predicted$Solar.R<-unname(lpmat_Solar.R%*%coef(model))[,1]
    predicted$Wind<-unname(lpmat_Wind%*%coef(model))[,1]

#obtain term predictions
    answerdf<-as.data.frame(predicted$predicted - predicted$Ozone)
    colnames(answerdf)<-"Ozone"
    answerdf$Solar.R<-(predicted$predicted - predicted$Solar.R)
    answerdf$Wind<-(predicted$predicted - predicted$Wind)

#visualize using visreg method and the alternative method above 
    visregdat<-visreg(model, "Ozone", plot=FALSE)$fit
    plot(visregFit~Ozone,data=visregdat, type="l", lwd=5, ylim=c(-30,90), ylab= "fitted values")
    points(answerdf$Ozone~air$Ozone, col="violet", pch=20)
    legend(100,60, legend=c("Visreg", "Alt. method"),
           col=c("black", "violet"), pch=20, cex=0.8)