\begin{Schunk}
\begin{Sinput}
 summary(mymod4)
\end{Sinput}
\begin{Soutput}
Call:
lm(formula = y ~ rcs(x, 10))

Residuals:
     Min       1Q   Median       3Q      Max 
-1.85094 -0.52619  0.07638  0.53238  1.94431 

Coefficients:
                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)           -0.6753     0.4438  -1.522 0.131605    
rcs(x, 10)x            4.9678     0.5578   8.905 5.42e-14 ***
rcs(x, 10)x'        -105.6228    19.3026  -5.472 3.97e-07 ***
rcs(x, 10)x''        257.8897   115.8651   2.226 0.028527 *  
rcs(x, 10)x'''      -176.5435   212.2693  -0.832 0.407782    
rcs(x, 10)x''''      135.7993   158.3145   0.858 0.393292    
rcs(x, 10)x'''''    -150.0714    62.0285  -2.419 0.017558 *  
rcs(x, 10)x''''''    108.2622    69.4949   1.558 0.122780    
rcs(x, 10)x'''''''  -430.5118   138.3122  -3.113 0.002486 ** 
rcs(x, 10)x''''''''  452.4003   118.7002   3.811 0.000253 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.7889 on 90 degrees of freedom
Multiple R-squared: 0.9428,	Adjusted R-squared: 0.9371 
F-statistic: 164.8 on 9 and 90 DF,  p-value: < 2.2e-16 
\end{Soutput}
\begin{Sinput}
 rm(mymod4, predict4, newx)
\end{Sinput}
\end{Schunk}
