Hi,

I am trying to run a regression analysis on my GAM model in R and am using the blog DataTechNotes as a guide (Link: DataTechNotes: GAM (Generalized Additive Model) Regression Example with R).

In the example from the blog, they created a GAM model using the following code to create their GAM model

```
bgam=gam(medv~s(rm)+s(lstat)+ptratio+indus+crim+zn+age, data=boston)
```

Similarly, I used the following code to create my GAM model

```
preGAM=gam(preOutlierRem.dat$DailyIncrease ~ s(preOutlierRem.dat$Precipitation))
```

When they view the summary their GAM model using the code

```
summary(bgam)
```

They receive the following output which shows the estimate of parametric coefficients (shown below)

```
Family: gaussian
Link function: identity
Formula:
medv ~ s(rm) + s(lstat) + ptratio + indus + crim + zn + age
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 31.54656 2.08187 15.153 < 2e-16 ***
ptratio -0.52355 0.10112 -5.178 3.29e-07 ***
indus 0.00383 0.04052 0.095 0.9247
crim -0.13005 0.02498 -5.207 2.84e-07 ***
zn -0.01682 0.01065 -1.579 0.1150
age 0.01848 0.01055 1.751 0.0806 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Approximate significance of smooth terms:
edf Ref.df F p-value
s(rm) 6.514 7.680 24.30 2e-16 ***
s(lstat) 6.272 7.451 34.29 2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.807 Deviance explained = 81.4%
GCV = 16.948 Scale est. = 16.319 n = 506```
```

However, when I view the summary of my GAM model using the code:

```
summary(preGAM)
```

I receive a similar output (shown below), however, my output only shows the intercept and does not show the parametric coefficients that are shown in the example

```
Family: gaussian
Link function: identity
Formula:
postOutlierRem.dat$DailyIncrease ~ s(postOutlierRem.dat$Precipitation)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.102905 0.009653 10.66 <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(postOutlierRem.dat$Precipitation) 8.934 8.999 413.6 <2e-16
s(postOutlierRem.dat$Precipitation) ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.872 Deviance explained = 87.4%
GCV = 0.052103 Scale est. = 0.05116 n = 549```
```

How do I find the estimate for the coefficient "Precipitation" in my model? I want to be able to run two different GAM models and see how the estimate of the coefficient "Precipitation" varies between my two models. I appreciate any feedback that anyone has. TIA.