Smooth constructor for monotonic P-splines

The function sets up a smooth term for shape constraint estimation of P-spline model terms. Note that this currently only works using boosting and backfitting.

# S3 method for ms.smooth.spec
smooth.construct(object, data, knots, ...)

Arguments

object

Either a smooth specification object, or object of class "bamlss", "bamlss.frame", "bamlss.formula" or "bamlss.terms". For smooth specification objects, see function smooth.construct.

data

A data frame or list, see also see function smooth.construct.

knots

See function smooth.construct.

...

Arguments passed to the smooth term constructor functions.

Value

See function see smooth.construct.

See also

bamlss.frame, bamlss.formula, bamlss, smooth.construct.

Examples

if (FALSE) ## Generate some data.
set.seed(123)

n <- 300
x <- runif(n, -2, 3)
y <- sin(x) + rnorm(n, sd = 0.1)

d <- data.frame("y" = y, "x" = x)

## Increasing: constr = 1.
## Decreasing: constr = 2.
b <- bamlss(y ~ s2(x,bs="ms",xt=list(constr=1)),
  data = d, optimizer = opt_bfit, sampler = sam_MVNORM)
#> AICc 160.7101 logPost -94.9489 logLik -75.1264 edf 5.1219 eps 0.8913 iteration   1
#> AICc  -6.5555 logPost -11.0618 logLik   8.8436 edf 5.4463 eps 0.1834 iteration   2
#> AICc -75.1945 logPost  23.4106 logLik  43.4027 edf 5.6763 eps 0.1043 iteration   3
#> AICc -84.3641 logPost  28.0615 logLik  48.1083 edf 5.7921 eps 0.0406 iteration   4
#> AICc -84.4774 logPost  28.1376 logLik  48.2034 edf 5.8289 eps 0.0061 iteration   5
#> AICc -84.4729 logPost  28.1377 logLik  48.2058 edf 5.8334 eps 0.0002 iteration   6
#> AICc -84.4728 logPost  28.1377 logLik  48.2059 edf 5.8335 eps 0.0000 iteration   7
#> AICc -84.4728 logPost  28.1377 logLik  48.2059 edf 5.8335 eps 0.0000 iteration   7
#> elapsed time:  0.02sec
#> 
#> Warning: sigma is numerically not positive semidefinite

## Predict and plot.
p <- predict(b, model = "mu", FUN = c95)
plot(y ~ x)
plot2d(p ~ x, add = TRUE, col.lines = 4, lwd = 2)