derivative.scam: Derivative of the univariate smooth model terms

View source: R/derivative.scam.r

derivative.scamR Documentation

Derivative of the univariate smooth model terms

Description

Function to get derivatives of the smooth model terms (currently only of the univariate smooths). Analytical derivatives for SCOP-splines (shape constrained P-splines), finite difference approximation is used for all others

Usage

derivative.scam(object,smooth.number=1,deriv=1)

Arguments

object

fitted scam object

smooth.number

ordered number of the smooth model term (1,2,...), ordered as in the formula, which derivative is needed to be calculated.

deriv

either 1 if the 1st derivative is required, or 2 if the 2nd

Value

d

values of the derivative of the smooth term.

se.d

standard errors of the derivative.

Author(s)

Natalya Pya <nat.pya@gmail.com>

References

Pya, N. and Wood, S.N. (2015) Shape constrained additive models. Statistics and Computing, 25(3), 543-559

See Also

scam

Examples


 set.seed(2)
n <- 200
x1 <- runif(n)*4-1;
f1 <- exp(4*x1)/(1+exp(4*x1)) # monotone increasing smooth
x2 <- sort(runif(n)*3-1)      # decreasing smooth
f2 <- exp(-1.3*x2)
f <- f1+ f2 
y <- f+ rnorm(n)*0.2
## fit model, results, and plot...
b <- scam(y~ s(x1,k=20,bs="mpi")+s(x2,k=15,bs="mpd"))

d1 <- derivative.scam(b,smooth.number=1,deriv=1)

par(mfrow=c(1,2))

xx <- sort(x1,index=TRUE)
plot(xx$x,d1$d[xx$ix],type="l",xlab=expression(x[1]),
     ylab=expression(df[1]/dx[1]))

d2 <- derivative.scam(b,smooth.number=2,deriv=1)

xx <- sort(x2,index=TRUE)
plot(xx$x,d2$d[xx$ix],type="l",xlab=expression(x[2]),
     ylab=expression(df[2]/dx[2]))


scam documentation built on June 22, 2024, 10:43 a.m.