Perform the following step to diagnose the generalized additive model:

1. Generate the diagnostic plot using gam.check on the fitted model:

        > gam.check(fit)
        Output:
        Method: GCV Optimizer: magic
        Smoothing parameter selection converged after 7 iterations.
        The RMS GCV score gradient at convergence was 8.79622e-06 .
        The Hessian was positive definite.
        The estimated model rank was 10 (maximum possible: 10)
        Model rank = 10 / 10 

        Basis dimension (k) checking results. Low p-value (k-index<1) may
        indicate that k is too low, especially if edf is close to k'.

                  k' edf k-index p-value
        s(nox) 9.000 8.434 0.397 0