caps {dplR} | R Documentation |
Applies a smoothing spline to y
with rigidity determined
by two parameters: frequency response f
at a wavelength
of nyrs
years.
caps(y, nyrs = length(y)/2, f = 0.5)
y |
a |
nyrs |
a number greater than 1, affecting the rigidity of the
spline. When |
f |
a number between 0 and 1 giving the frequency response at a
wavelength of |
This applies the classic smoothing spline from Cook and Peters (1981). The rigidity of the spline has a frequency response of 50% at a wavelength of nyrs
. The references, of course, have more information.
This funciton was introduced to dplR
in version 1.7.3 and essentially replaces ffcsaps
for most uses. Where ffcsaps
is written entirely in R, caps
is a wrapper for a Fortran subroutine from Ed Cook's ARSTAN program that is thousands of times faster.
Note: like ffcsaps
, caps
returns NA
if there are any NA
values in y
. See examples.
A filtered vector.
Fotran code provided by Ed Cook and adapted for dplR by Andy Bunn.
Cook, E. R. and Kairiukstis, L. A., editors (1990) Methods of Dendrochronology: Applications in the Environmental Sciences. Springer. ISBN-13: 978-0-7923-0586-6.
Cook, E. R. and Peters, K. (1981) The Smoothing Spline: A New Approach to Standardizing Forest Interior Tree-Ring Width Series for Dendroclimatic Studies. Tree-Ring Bulletin, 41, 45-53.
library(graphics)
library(utils)
## Use first series from the Mesa Verde data set
data(co021)
series <- co021[, 1]
series <- series[!is.na(series)]
plot(series, type = "l", ylab = "Ring Width (mm)", col = "grey")
lines(caps(series, nyrs = 10), col = "red", lwd = 2)
lines(caps(series, nyrs = 100), col = "green", lwd = 2)
## nyrs defaults to 0.5*length(series) = 347
lines(caps(series), col = "blue", lwd = 2)
legend("topright",
c("Series", "nyrs=10", "nyrs=100",
paste("Default nyrs (", length(series) / 2, ")", sep="")),
fill=c("grey", "red", "green", "blue"))
## Compare to ffcsaps
all.equal(caps(series),ffcsaps(series))
## Note behavior when NA is encountered and
## take appropriate measures as demonstrated above
y <- c(NA,NA,rnorm(100))
caps(y)