```
# creating a linear + linear function
x <- seq(0,10, length.out=201)
knot <- 5
set.seed(12543)
mu <- ifelse(x<=knot,5+0.5*x,5+0.5*x+(x-knot))
y <- rNO(201, mu=mu, sigma=.5)
# plot the data
plot(y~x, xlim=c(-1,13), ylim=c(3,18))
# fit model using fixed break points
m1 <- fitFixedKnots(y, x, knots=5, degree=1)
knots(m1)
lines(fitted(m1)~x, col="red")
# now estimating the knot
m2 <- fitFreeKnots(y, x, knots=5, degree=1)
knots(m2)
summary(m2)
# now predicting
plot(y~x, xlim=c(-5,13), ylim=c(3,18))
lines(fitted(m2)~x, col="green", lwd=3)
points(-2:13,predict(m2, newdata=-2:13), col="red",pch = 21, bg="blue")
points(-2:13,predict(m2, newdata=-2:13, old.x.range=FALSE), col="red",pch = 21, bg="grey")
# fit different basis
m21 <- fitFreeKnots(y, x, knots=5, degree=1, base="Bbase")
deviance(m2)
deviance(m21) # should be identical
# predicting with m21
plot(y~x, xlim=c(-5,13), ylim=c(3,18))
lines(fitted(m21)~x, col="green", lwd=3)
points(-2:13,predict(m21, newdata=-2:13), col="red",pch = 21, bg="blue")
points(-2:13,predict(m21, newdata=-2:13, old.x.range=FALSE), col="red",pch = 21, bg="grey")
```

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