Nothing

```
###
### Ramsay, Hooker & Graves (2009)
### Functional Data Analysis with R and Matlab (Springer)
###
# Remarks and disclaimers
# These R commands are either those in this book, or designed to
# otherwise illustrate how R can be used in the analysis of functional
# data.
# We do not claim to reproduce the results in the book exactly by these
# commands for various reasons, including:
# -- the analyses used to produce the book may not have been
# entirely correct, possibly due to coding and accuracy issues
# in the functions themselves
# -- we may have changed our minds about how these analyses should be
# done since, and we want to suggest better ways
# -- the R language changes with each release of the base system, and
# certainly the functional data analysis functions change as well
# -- we might choose to offer new analyses from time to time by
# augmenting those in the book
# -- many illustrations in the book were produced using Matlab, which
# inevitably can imply slightly different results and graphical
# displays
# -- we may have changed our minds about variable names. For example,
# we now prefer "yearRng" to "yearRng" for the weather data.
# -- three of us wrote the book, and the person preparing these scripts
# might not be the person who wrote the text
# Moreover, we expect to augment and modify these command scripts from time
# to time as we get new data illustrating new things, add functionality
# to the package, or just for fun.
###
### ch. 2. Essential Comparisons of the Matlab and R Languages
###
# load the fda package
library(fda)
# display the data files associated with the fda package
data(package='fda')
# start the HTML help system if you are connected to the Internet, in
# order to open the R-Project documentation index page in order to obtain
# information about R or the fda package.
help.start()
##
## Section 2.1 A Quick Comparison of Matlab and R Syntax
##
# Names with periods:
min.fourier.basis = create.fourier.basis()
# structure of this fourier basis object:
str(min.fourier.basis)
# One component of this list of class 'basisfd'
min.fourier.basis$type
# create a vector
rng = c(0, 1)
# Access a component of a vector
rng[2]
# Logical values:
TRUE
FALSE
# T and F are variables
# by default are TRUE and FALSE, respectively,
T
F
# but can be redefined:
F = TRUE
if(F)cat('TRUE')
# alternative
F = c('Do', 'not', 'use', 'F', 'as', 'a', 'logical.')
# The following will now throw an error, and illustrates why only
# TRUE and FALSE ought to be used as logical constants:
# if (F) cat('TRUE')
# addition?
1 + TRUE # = 2
# Any line that is not syntactically complete
# is assumed to continue to the next line
c("like",
'This')
"line can end in ';'";
"but not required."
# Section 2.1.2. Using Functions
b3.4 = create.bspline.basis(norder=3, breaks=c(0, .5, 1))
fdPar3 = fdPar(b3.4, lambda=1)
fd3.4s0 = smooth.basis(0:1, 0:1, fdPar3)
class(fd3.4s0) # fdSmooth
# its 'fd' component
myfdobj. = fd3.4s0$fd
# or directly with the function call in one line
myfdobj = smooth.basis(0:1, 0:1, fdPar3)$fd
all.equal(myfdobj., myfdobj)
fd3.4s0$gcv
# specifying arguments by name not in the standard order
myfdobj = smooth.basis(y=c(1,1,2), argvals=seq(0, 1, .5), fdPar3)$fd
##
## Section 2.2 Singleton Index Issues
##
temp = matrix(c(1,2,3,4),2,2)
class(temp)
class(temp[,1])
temp[,1] # not a matrix
temp[,1, drop=FALSE] # still a matrix
index = 1:2
temp[, index] # matrix
index = 1
temp[, index] # not a matrix
index = 1:2
temp[, index][, 1] # OK
index = 1
# temp[, index][, 1] # Error
# 3-d array
A = array(1:2, dim=c(1, 2, 1))
a1 = A[, 1, ] # scalar
dim(a1)= dim(A)[-2]
a1 # 1 x 1 matrix
##
## Section 2.3 Classes and Objects in R and Matlab
##
default.fd = fd()
is.list(default.fd)
class(default.fd$basis)
plot(default.fd)
# same as
plot.fd(default.fd)
attributes(default.fd)
coef(default.fd)
# same as
default.fd$coefs
# fdPar example
rangeval = c(-3,3)
x = rnorm(50)
x[x < -3] = -2.99
x[x > 3] = 2.99
basisobj = create.bspline.basis(rangeval, 11)
Wfd0 = fd(matrix(0,11,1), basisobj)
WfdParobj = fdPar(Wfd0)
coef(WfdParobj)
WfdParobj$coefs # NULL
WfdParobj$fd$coefs # OK
# str = structure
str(WfdParobj)
# All methods for the generic function 'coef' in attached packages
methods(coef)
library('nlme')
# add 'coef' methods for objects defined in the 'nlme' package
methods(coef)
methods(class='fd') # methods for objects of class 'fd'
##
## Section 2.4 More to Read
##
```

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