Please see help("mgcv-FAQ") number 2
best,
simon
On 06/19/2012 05:27 PM, Stefano Sofia wrote:> Given
>
> model1<- gam(Y ~ X1, family=poisson)
>
> (which is a glm), the regression equation is
>
> Log(Y) = 2.132 + 0.00044 X1
>
> In fact from summary(model1), I read
>
>> summary(model1)
> Family: poisson
> Link function: log
> ...
> Parametric coefficients:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) 2.132e+00 1.018e-01 20.949< 2e-16 ***
> X1 4.406e-04 5.395e-05 8.165 3.21e-16 ***
> ...
>
> But if I use
> model2<- gam(Y ~ s(X1), family=poisson)
>
> how can I write the regression equation? Summary(model2) is
>
>> summary(model2)
> Family: poisson
> Link function: log
>
> Formula:
> Y ~ s(X1)
> <environment: 0x43c02e0>
>
> Parametric coefficients:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) 2.55268 0.06782 37.64<2e-16 ***
> ---
> Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
>
> Approximate significance of smooth terms:
> edf Ref.df Chi.sq p-value
> s(X1) 3.967 4.85 71.1 4.86e-14 ***
> ---
> Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
>
> R-sq.(adj) = 0.885 Deviance explained = 87.2%
> UBRE score = 0.13791 Scale est. = 1 n = 20
>
>
> Thank you for your help
> Stefano Sofia
>
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