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I want to evaluate each component of the predictor from a GAM model separately using the option type="terms". As a sanity check, I compared the results to an evaluation of the total prediction using the option type="response".

It turns out that the results differ. Here is an example: 

library(mgcv)
n<-200
sig <- 2
dat <- gamSim(1,n=n,scale=sig)
b<-gam(y~x0+s(I(x1^2))+s(x2)+offset(x3),da=dat)

nd <- data.frame(x0=c(.25,.5),x1=c(.25,.5),x2=c(.25,.5),x3=c(.25,.5))

a1 <- predict.gam(b,newdata=nd,type="response") 
a2 <- rowSums(predict.gam(b,newdata=nd,type="terms")) + b$coefficients[1]
a1 - a2 # Should be zero!
#    1    2 
# 0.25 0.50

Can anyone help me with this problem? Thank you very much for your help!

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1 に答える 1

3

あなたのモデル:

y ~ x0 + s(I(x1^2)) + s(x2) + offset(x3)

オフセット項があります。

オフセットはpredict.gamwhentype = "link"またはtype = "response"で考慮されますが、 when では考慮されませんtype = "terms"。

a1 <- predict.gam(b, newdata=nd, type="response")
#        1         2 
#11.178280  6.865068 

a2 <- predict.gam(b, newdata=nd, type="terms")
#           x0 s(I(x1^2))      s(x2)
#1 0.006878346 -1.8710120  5.6467813
#2 0.013756691 -0.6037635 -0.1905571
#attr(,"constant")
#(Intercept) 
#   7.145632

したがって、オフセットを自分で追加する必要があります。

a2 <- rowSums(a2) + b$coef[1] + nd$x3
#        1         2 
#11.178280  6.865068

今a1とa2は同じです。

ご参考までに、次のドキュメントを参照してください?predict.gam。

type: ... When ‘type="terms"’ each component of the linear
      predictor is returned seperately (possibly with standard
      errors): this includes parametric model components, followed
      by each smooth component, **but excludes any offset and any
      intercept**.
于 2016-07-24T19:31:10.120 に答える