plot.basisfd | R Documentation |
Plots all the basis functions.
## S3 method for class 'basisfd'
plot(x, knots=TRUE, axes=NULL, ...)
x |
a basis object |
knots |
logical: If TRUE and x[['type']] == 'bspline', the knot locations are plotted using vertical dotted, red lines. Ignored otherwise. |
axes |
Either a logical or a list or
|
... |
additional plotting parameters passed to |
none
a plot of the basis functions
Ramsay, James O., Hooker, Giles, and Graves, Spencer (2009), Functional data analysis with R and Matlab, Springer, New York.
Ramsay, James O., and Silverman, Bernard W. (2005), Functional Data Analysis, 2nd ed., Springer, New York.
Ramsay, James O., and Silverman, Bernard W. (2002), Applied Functional Data Analysis, Springer, New York.
plot.fd
oldpar <- par(no.readonly=TRUE)
##
## 1. b-spline
##
# set up the b-spline basis for the lip data, using 23 basis functions,
# order 4 (cubic), and equally spaced knots.
# There will be 23 - 4 = 19 interior knots at 0.05, ..., 0.95
lipbasis <- create.bspline.basis(c(0,1), 23)
# plot the basis functions
plot(lipbasis)
##
## 2. Fourier basis
##
yearbasis3 <- create.fourier.basis(c(0,365),
axes=list("axesIntervals") )
# plot the basis
plot(yearbasis3)
##
## 3. With Date and POSIXct rangeval
##
# Date
July4.1776 <- as.Date('1776-07-04')
Apr30.1789 <- as.Date('1789-04-30')
AmRev <- c(July4.1776, Apr30.1789)
BspRevolution <- create.bspline.basis(AmRev)
plot(BspRevolution)
# POSIXct
July4.1776ct <- as.POSIXct1970('1776-07-04')
Apr30.1789ct <- as.POSIXct1970('1789-04-30')
AmRev.ct <- c(July4.1776ct, Apr30.1789ct)
BspRev.ct <- create.bspline.basis(AmRev.ct)
plot(BspRev.ct)
par(oldpar)
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