## 构建GAM模型
mgam<-gam(log(CPUE+1)~s(sst)+s(ssh)+s(sss)+s(stg)+,data=trainset,model=T)
summary(mgam)
##运行结果
Family: gaussian
Link function: identity
Formula:
log(CPUE + 1) ~ s(sst) + s(ssh) + s(sss) + s(stg)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6.11369 0.07581 80.65 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Approximate significance of smooth terms:
edf Ref.df F p-value
s(sst) 7.603 8.505 5.034 5.51e-06 ***
s(ssh) 5.255 6.430 3.018 0.00568 **
s(sss) 2.139 2.692 4.305 0.00740 **
s(stg) 2.032 2.584 0.904 0.44626
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.21 Deviance explained = 24.7%
GCV = 2.2236 Scale est. = 2.1147 n = 368


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