```
if (FALSE) {
############################################################
## Do not run these examples automatically as they take
## some time (~ 30 seconds depending on the system)
### a simple linear example
set.seed(1907)
data <- data.frame(x1 = rnorm(100), x2 = rnorm(100),
z = factor(sample(1:3, 100, replace = TRUE)))
data$y <- rnorm(100, mean = data$x1 - data$x2 - 1 * (data$z == 2) +
1 * (data$z == 3), sd = 0.1)
linmod <- glmboost(y ~ x1 + x2 + z, data = data,
control = boost_control(mstop = 200))
## compute confidence interval from 10 samples. Usually one should use
## at least 1000 samples.
CI <- confint(linmod, B = 10, level = 0.9)
CI
## to compute a confidence interval for another level simply change the
## level in the print function:
print(CI, level = 0.8)
## or print a subset (with point estimates):
print(CI, level = 0.8, pe = TRUE, which = "z")
### a simple smooth example
set.seed(1907)
data <- data.frame(x1 = rnorm(100), x2 = rnorm(100))
data$y <- rnorm(100, mean = data$x1^2 - sin(data$x2), sd = 0.1)
gam <- gamboost(y ~ x1 + x2, data = data,
control = boost_control(mstop = 200))
## compute confidence interval from 10 samples. Usually one should use
## at least 1000 samples.
CI_gam <- confint(gam, B = 10, level = 0.9)
par(mfrow = c(1, 2))
plot(CI_gam, which = 1)
plot(CI_gam, which = 2)
## to compute a confidence interval for another level simply change the
## level in the plot or lines function:
lines(CI_gam, which = 2, level = 0.8)
}
```

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