Chapter 18 Appendix D Function and variable index

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Index Entry

Section

!:

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

<:

>:

?:

^:

|:

Conditional execution

~:

Formulae for statistical models

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

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

boxplot:

One- and two-sample tests

break:

Repetitive execution

bruto:

Some non-standard models

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

Displaying multivariate data

Frequency tables from factors

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

Updating fitted models

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

F:

Examining the distribution of a set of data

for:

Repetitive execution

formula:

Generic functions for extracting model information

function:

Writing your own functions

Examining the distribution of a set of data

hist:

Display graphics

identify:

Interacting with graphics

if:

Conditional execution

if:

Conditional execution

ifelse:

Conditional execution

Examining the distribution of a set of data

legend:

Low-level plotting commands

length:

Vector arithmetic

length:

The intrinsic attributes mode and length

levels:

Factors

lines:

Low-level plotting commands

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

mars:

Some non-standard models

The intrinsic attributes mode and length

Nonlinear least squares and maximum likelihood models

Some non-standard models

nlminb:

Nonlinear least squares and maximum likelihood models

nrow:

Matrix facilities

optim:

Nonlinear least squares and maximum likelihood models

The outer product of two arrays

pairs:

Displaying multivariate data

Generic functions for extracting model information

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

qqline:

Examining the distribution of a set of data

qqline:

Display graphics

qqnorm:

Examining the distribution of a set of data

Least squares fitting and the QR decomposition

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

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

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:

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

unclass:

The class of an object

update:

Updating fitted models

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

while:

Repetitive execution

wilcox.test:

One- and two-sample tests

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