Compute 95% Credible Interval and Mean

Small helper function that computes the 2.5% and 97.5% quantiles and the mean of a vector. Useful for example when using function predict.bamlss.

c95(x)

Arguments

x	A numeric vector.

See also

predict.bamlss, coef.bamlss

Examples

x <- rnorm(100)
c95(x)
#>        2.5%        Mean       97.5% 
#> -1.94606577 -0.04686997  1.76888364 

# NOT RUN {
## Example computing predictions.
set.seed(123)
d <- data.frame("x" = seq(-3, 3, length = 30))
d$y <- sin(d$x) + rnorm(30, sd = 0.3)

## Estimate model and compute predictions.
## with c95().
b <- bamlss(y ~ s(x), data = d)
p <- predict(b, model = "mu", FUN = c95)
plot(d)
matplot(d$x, p, type = "l", lty = c(2, 1, 2),
  col = "black", add = TRUE)

## Example extracting coefficients.
coef(b, FUN = c95)
# }