scam (version 1.2-17)

derivative.scam: 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)

Value

d

values of the derivative of the smooth term.

se.d

standard errors of the derivative.

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

Author

Natalya Pya <[e-mail]>

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]))