Appendix D — Function and variable index

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	Index Entry		Section
!
	!:		Logical vectors
	!=:		Logical vectors
%
	%*%:		Multiplication
	%o%:		The outer product of two arrays
&
	&:		Logical vectors
	&&:		Conditional execution
*
	*:		Vector arithmetic
+
	+:		Vector arithmetic
-
	-:		Vector arithmetic
.
	.:		Updating fitted models
	.First:		Customizing the environment
	.Last:		Customizing the environment
/
	/:		Vector arithmetic
:
	::		Generating regular sequences
	:::		Namespaces
	::::		Namespaces
<
	<:		Logical vectors
	<<-:		Scope
	<=:		Logical vectors
=
	==:		Logical vectors
>
	>:		Logical vectors
	>=:		Logical vectors
?
	?:		Getting help
	??:		Getting help
^
	^:		Vector arithmetic
|
	|:		Logical vectors
	||:		Conditional execution
~
	~:		Formulae for statistical models
A
	abline:		Low-level plotting commands
	ace:		Some non-standard models
	add1:		Updating fitted models
	anova:		Generic functions for extracting model information
	anova:		ANOVA tables
	aov:		Analysis of variance and model comparison
	aperm:		Generalized transpose of an array
	array:		The array() function
	as.data.frame:		Making data frames
	as.vector:		The concatenation function c() with arrays
	attach:		attach() and detach()
	attr:		Getting and setting attributes
	attr:		Getting and setting attributes
	attributes:		Getting and setting attributes
	attributes:		Getting and setting attributes
	avas:		Some non-standard models
	axis:		Low-level plotting commands
B
	boxplot:		One- and two-sample tests
	break:		Repetitive execution
	bruto:		Some non-standard models
C
	c:		Vectors and assignment
	c:		Character vectors
	c:		The concatenation function c() with arrays
	c:		Concatenating lists
	C:		Contrasts
	cbind:		Forming partitioned matrices
	coef:		Generic functions for extracting model information
	coefficients:		Generic functions for extracting model information
	contour:		Display graphics
	contrasts:		Contrasts
	coplot:		Displaying multivariate data
	cos:		Vector arithmetic
	crossprod:		Index matrices
	crossprod:		Multiplication
	cut:		Frequency tables from factors
D
	data:		Accessing builtin datasets
	data.frame:		Making data frames
	density:		Examining the distribution of a set of data
	det:		Singular value decomposition and determinants
	detach:		attach() and detach()
	determinant:		Singular value decomposition and determinants
	dev.list:		Multiple graphics devices
	dev.next:		Multiple graphics devices
	dev.off:		Multiple graphics devices
	dev.prev:		Multiple graphics devices
	dev.set:		Multiple graphics devices
	deviance:		Generic functions for extracting model information
	diag:		Multiplication
	dim:		Arrays
	dotchart:		Display graphics
	drop1:		Updating fitted models
E
	ecdf:		Examining the distribution of a set of data
	edit:		Editing data
	eigen:		Eigenvalues and eigenvectors
	else:		Conditional execution
	Error:		Analysis of variance and model comparison
	example:		Getting help
	exp:		Vector arithmetic
F
	F:		Logical vectors
	factor:		Factors
	FALSE:		Logical vectors
	fivenum:		Examining the distribution of a set of data
	for:		Repetitive execution
	formula:		Generic functions for extracting model information
	function:		Writing your own functions
G
	getAnywhere:		Object orientation
	getS3method:		Object orientation
	glm:		The glm() function
H
	help:		Getting help
	help:		Getting help
	help.search:		Getting help
	help.start:		Getting help
	hist:		Examining the distribution of a set of data
	hist:		Display graphics
I
	identify:		Interacting with graphics
	if:		Conditional execution
	if:		Conditional execution
	ifelse:		Conditional execution
	image:		Display graphics
	is.na:		Missing values
	is.nan:		Missing values
J
	jpeg:		Device drivers
K
	ks.test:		Examining the distribution of a set of data
L
	legend:		Low-level plotting commands
	length:		Vector arithmetic
	length:		The intrinsic attributes mode and length
	levels:		Factors
	lines:		Low-level plotting commands
	list:		Lists
	lm:		Linear models
	lme:		Some non-standard models
	locator:		Interacting with graphics
	loess:		Some non-standard models
	loess:		Some non-standard models
	log:		Vector arithmetic
	lqs:		Some non-standard models
	lsfit:		Least squares fitting and the QR decomposition
M
	mars:		Some non-standard models
	max:		Vector arithmetic
	mean:		Vector arithmetic
	methods:		Object orientation
	min:		Vector arithmetic
	mode:		The intrinsic attributes mode and length
N
	NA:		Missing values
	NaN:		Missing values
	ncol:		Matrix facilities
	next:		Repetitive execution
	nlm:		Nonlinear least squares and maximum likelihood models
	nlm:		Least squares
	nlm:		Maximum likelihood
	nlme:		Some non-standard models
	nlminb:		Nonlinear least squares and maximum likelihood models
	nrow:		Matrix facilities
O
	optim:		Nonlinear least squares and maximum likelihood models
	order:		Vector arithmetic
	ordered:		Ordered factors
	ordered:		Ordered factors
	outer:		The outer product of two arrays
P
	pairs:		Displaying multivariate data
	par:		The par() function
	paste:		Character vectors
	pdf:		Device drivers
	persp:		Display graphics
	plot:		Generic functions for extracting model information
	plot:		The plot() function
	pmax:		Vector arithmetic
	pmin:		Vector arithmetic
	png:		Device drivers
	points:		Low-level plotting commands
	polygon:		Low-level plotting commands
	postscript:		Device drivers
	predict:		Generic functions for extracting model information
	print:		Generic functions for extracting model information
	prod:		Vector arithmetic
Q
	qqline:		Examining the distribution of a set of data
	qqline:		Display graphics
	qqnorm:		Examining the distribution of a set of data
	qqnorm:		Display graphics
	qqplot:		Display graphics
	qr:		Least squares fitting and the QR decomposition
	quartz:		Device drivers
R
	range:		Vector arithmetic
	rbind:		Forming partitioned matrices
	read.table:		The read.table() function
	rep:		Generating regular sequences
	repeat:		Repetitive execution
	resid:		Generic functions for extracting model information
	residuals:		Generic functions for extracting model information
	rlm:		Some non-standard models
	rm:		Data permanency and removing objects
S
	scan:		The scan() function
	sd:		The function tapply() and ragged arrays
	search:		Managing the search path
	seq:		Generating regular sequences
	shapiro.test:		Examining the distribution of a set of data
	sin:		Vector arithmetic
	sink:		Executing commands from or diverting output to a file
	solve:		Linear equations and inversion
	sort:		Vector arithmetic
	source:		Executing commands from or diverting output to a file
	split:		Repetitive execution
	sqrt:		Vector arithmetic
	stem:		Examining the distribution of a set of data
	step:		Generic functions for extracting model information
	step:		Updating fitted models
	sum:		Vector arithmetic
	summary:		Examining the distribution of a set of data
	summary:		Generic functions for extracting model information
	svd:		Singular value decomposition and determinants
T
	T:		Logical vectors
	t:		Generalized transpose of an array
	t.test:		One- and two-sample tests
	table:		Index matrices
	table:		Frequency tables from factors
	tan:		Vector arithmetic
	tapply:		The function tapply() and ragged arrays
	text:		Low-level plotting commands
	title:		Low-level plotting commands
	tree:		Some non-standard models
	TRUE:		Logical vectors
U
	unclass:		The class of an object
	update:		Updating fitted models
V
	var:		Vector arithmetic
	var:		The function tapply() and ragged arrays
	var.test:		One- and two-sample tests
	vcov:		Generic functions for extracting model information
	vector:		Vectors and assignment
W
	while:		Repetitive execution
	wilcox.test:		One- and two-sample tests
	windows:		Device drivers
X
	X11:		Device drivers

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