General Index

A

Addition

matrices, 68

order of operation, 36

vectors, 44–45

Aggregation

in data.table package, 135–138

groups, 120–123

AICC, 320

Akaike Information Criterion (AIC), 255–257, 259–260

@aliases tag, 382

all.obs option, 196

Ampersands (&) in compound tests, 111

Analysis of variance (ANOVA)

alternative to, 214–216

cross-validation, 259–260

model comparisons, 254

overview, 207–210

And operator in compound tests, 111–112

Andersen-Gill analysis, 244–245

Angle brackets (<>)

packages, 375

regular expressions, 169

ANOVA. See Analysis of variance (ANOVA)

Ansari-Bradley test, 204

Appearance options, 21–22

Appending elements to lists, 68

apt-get mechanism, 2

Arguments

C++ code, 385

CSV files, 74

functions, 49, 100–102

ifelse, 110

package documentation, 380

Arithmetic mean, 187

ARMA model, 315

Arrays, 71–72

Assigning variables, 36–37

Asterisks (*)

Markdown, 368

multiple regression, 228

NAMESPACE file, 377

vectors, 44

Attributes for data.frame, 54

Author information

LATEX documents, 360

packages, 375

@author tag, 382

Autocompleting code, 15–16

Autocorrelation, 318

Autoregressive (AR) moving averages, 315–322

Average linkage methods, 352, 355

Axes in nonlinear least squares model, 298

B

Back ticks ( ` ) with functions, 49

Backslashes () in regular expressions, 166

Base graphics, 83–84

boxplots, 85–86

histograms, 84

scatterplots, 84–85

Bayesian Information Criterion (BIC), 255–257, 259

Bayesian shrinkage, 290–294

Beamer mode in LATEX, 369

Beginning of lines in regular expressions, 167

Bell curve, 171

Bernoulli distribution, 176

Beta distribution, 185–186

BIC (Bayesian Information Criterion), 255–257, 259

Binary files, 77–79

Binomial distribution, 176–181, 185–186

Bioconductor, 373

BitBucket repositories, 25, 31

Books, 394

bootstrap, 262–265

Boxplots

ggplot2, 91–94

overview, 85–86

break statement, 115–116

Breakpoints for splines, 302

Building packages, 383–384

Byte-compilation for packages, 376

ByteCompile field, 376

C

C++ code, 384–383

package compilation, 387–390

sourceCpp function, 385–387

cache option for knitr chunks, 365

Calling functions, 49

arguments, 100

C++, 384

conflicts, 33

Carets (^) in regular expressions, 167

Case sensitivity

characters, 40

package names, 384

regular expressions, 162

variable names, 38

Cauchy distribution, 185–186

Cauchy priors in Bayesian shrinkage, 293–294

Causation vs. correlation, 199

Censored data in survival analysis, 240–241

Centroid linkage methods, 352, 355

Change Install Location option, 9

character data, 40

Charts, 329

chartsnthings site, 393

Chi-Squared distribution, 185–186

Chunks

LATEX program, 362–365

Markdown, 368

Citations in LATEX documents, 366

Classification trees, 311

Clusters, 337

hierarchical, 352–357

K-means algorithm, 337–345

PAM, 345–352

registering, 283

code

autocompleting, 15–16

C++, 384–390

indenting, 99

running in parallel, 282

Code Editing options, 21

Coefficient plots

Bayesian shrinkage, 292–294

Elastic Net, 289–290

logistic regression, 236

model comparisons, 253–254

multiple regression, 226–228, 230–231

Poisson regression, 237–240

residuals, 247, 249

VAR, 324–325

Collate field for packages, 375–376

Colons (:)

vectors, 44–45

Color

boxplots, 92

K-means algorithm, 339, 341

LATEX documents, 362

line graphs, 96

PAM, 350–351

scatterplots, 88–90

Column index for arrays, 71

Columns

cbind and rbind, 141–142

data.frame, 53, 58

data.table, 131–133

matrices, 68–70

Comma separated files (CSVs), 73–74

Command line interface, 14–15

comment option, 365

Comments, 46

knitr chunks, 365

package documentation, 381

Community edition, 10–11

Comparing

models, 253–257

multiple groups, 207–210

multiple variables, 192

vectors, 46

Compilation in C++

code, 384

packages, 387–390

Complete linkage methods, 352, 355

complete.obs option, 196

Components, installing, 5

Compound tests, 111–112

Comprehensive R Archive Network (CRAN), 1, 29, 384

Concatenating strings, 155–156

Conferences, 393

Confidence intervals

ANOVA, 207–209, 215–216

bootstrap, 262, 264–265

Elastic Net, 277, 279

GAM, 310

multiple regression, 226

one-sample t-tests, 200–203

paired two-sample t-tests, 207

two-sample t-tests, 205–206

Control statements, 105

compound tests, 111–112

if and else, 105–108

ifelse, 109–111

switch, 108–109

Converting shapefile objects into data.frame, 349

Correlation and covariance, 191–200

Covariates in simple linear regression, 211

Cox proportional hazards model, 242–244

.cpp files, 386

CRAN (Comprehensive R Archive Network), 1, 29, 384

Create Project options, 16–17

Cross tables, 149

Cross-validation

Elastic Net, 276–277

overview, 257–262

CSVs (comma separated files), 73–74

Cubic splines, 302

Curly braces ({})

functions, 99

if and else, 106–107

regular expressions, 166

D

Data

censored, 240–241

missing. See Missing data

Data Analysis Using Regression and Multilevel/Hierarchical Models, 50, 291, 394

data folder, 373–374

data.frames, 53–61

converting shapefile objects into, 349

ddply function, 124, 126

Elastic Net, 272

joins, 145

merging, 143–144

Data Gotham conference, 393

Data meetups, 391

Data munging, 117

Data reshaping, 141

cbind and rbind, 141–142

joins, 142–149

reshape2 package, 149–153

Data structures, 53

arrays, 71–72

data.frame, 53–61

lists, 61–68

matrices, 68–71

Data types, 38

C++ code, 387

character, 40

dates, 40–41

logical, 41–43

matrices, 68

numeric, 38–39

vectors, 43–48

Databases, reading from, 75–76

Dates, 40–41

LATEX documents, 360

packages, 375

Decision trees, 310–312

DeclareGraphics Extensions, 360

Default arguments, 101–102

Degrees of freedom

ANOVA, 215

multiple regression, 225

splines, 300

t-tests, 201–202

Delimiters in CSV files, 74

Delta in model comparisons, 258

Dendrograms

ggplot2, 87–88

hierarchical clustering, 352

normal distribution, 172–173

Density plots, 87–88, 184, 207

Dependencies in packages, 30

Dependent variables in simple linear regression, 211

Depends field

C++ code, 386

packages, 375

Description field, 374–375

DESCRIPTION file, 374–377

@description tag, 382

Destination in installation, 4–5

@details tag, 382

dev option for knitr chunks, 365

Deviance in model comparisons, 256

Diffing process, 318–319

Dimensions in K-means algorithm, 339

direction argument, 265

Directories

creating, 18

installation, 4

names, 18

Distance between clusters, 352

Distance metric for K-means

algorithm, 337

Distributions. See Probability distributions

Division

matrices, 68

order of operation, 36

vectors, 44–45

Documentation

functions, 49

packages, 380–383

documentclass, 360

Documents as R resources, 394

Dollar signs ($)

data.frame, 56

multiple regression, 225

regular expressions, 167

%dopar% operator, 284

dot-dot-dot argument (...), 102

Downloading R, 1–2

DSN connections, 75

Dynamic Documents with R and knitr, 394

dzslides format, 369

E

echo option for knitr chunks, 365

EDA (Exploratory data analysis), 83, 199, 219

Elastic Net, 271–290

Elements of Statistical Learning: Data Mining, Inference, and Prediction, 394

End of lines in regular expressions, 167

engine option for knitr chunks, 365

Ensemble methods, 312

Environment, 13–14

command line interface, 14–15

RStudio. See RStudio overview

Equal to symbol (=)

if and else, 105

variable assignment, 36

Equality of matrices, 68

Esc key in command line commands, 15

eval option for knitr chunks, 365

everything option, 196

@examples tag, 382

Excel data, 74–75

Exclamation marks (!) in Markdown, 368

Expected value, 188

Experimental variables in simple linear regression, 211

Exploratory data analysis (EDA), 83, 199, 219

Exponential distribution, 185–186

Exponents, order of operation, 36

@export tag, 382

Expressions, regular, 161–169

Extra arguments, 102

Extracting

data from Websites, 80–81

text, 157–161

F

F distribution, 185–186

F-tests

ANOVA, 215

multiple regression, 225

simple linear regression, 214–215

two-sample, 204

faceted plots, 89–92

factor data type, 40

factors

as.numeric with, 160

Elastic Net, 273

storing, 60

vectors, 48

FALSE value

with if and else, 105–108

with logical operators, 41–43

fig.cap option, 365–366

fig.scap option, 365

fig.show option, 365

fill argument for histograms, 87

Fitted values against residuals plots, 249–251

folder structure, 373

for loops, 113–115

Forests, random, 312–313

formula interface

aggregation, 120–123

ANOVA, 208

Elastic Net, 272

logistic regression, 235–236

multiple regression, 224, 226, 230

scatterplots, 84–85

simple linear regression, 213

Formulas for distributions, 185–186

Frontend field for packages, 374

Functions

arguments, 100–102

assigned to objects, 99

C++, 384

calling, 49, 100

conflicts, 33

do.call, 104

documentation, 49

package documentation, 380

return values, 103

G

g++ compiler, 385

Gamma distribution, 185–186

Gamma linear model, 240

GAMs (generalized additive models), 304–310

Gap statistic in K-means algorithm, 343–344

Garbage collection, 38

GARCH (generalized autoregressive

conditional heteroskedasticity)

models, 327–336

Gaussian distribution, 171–176

gcc compiler, 385

General options for RStudio tools, 20–21

Generalized additive models (GAMs), 304–310

Generalized autoregressive conditional heteroskedasticity (GARCH) models, 327–336

Generalized linear models, 233

logistic regression, 233–237

miscellaneous, 240

Poisson regression, 237–240

Geometric distribution, 185–186

Git

integration with RStudio, 25–26

selecting, 19

Git/SVN option, 25

GitHub repositories, 25

for bugs, 392

package installation from, 31, 383

README files, 380

Graphics, 83

base, 83–86

ggplot2, 86–97

Greater than symbols (>)

if and else, 105

variable assignment, 37

Groups, 117

aggregation, 120–123

apply family, 117–120

comparing, 207–210

data.table package, 129–138

plyr package, 124–129

H

Hadoop framework, 117

Hartigan’s Rule, 340–342

Hash symbols (#)

comments, 46

Markdown, 368

package documentation, 381

pandoc, 369

header command in pandoc, 369

Heatmaps, 193

Hello, World! program, 99–100

Help pages in package documentation, 381

Hierarchical clustering, 352–357

Histograms, 84

bootstrap, 264

ggplot2, 87–88

multiple regression, 219

Poisson regression, 238

residuals, 253

Hotspot locations, 297–298

HTML tables, extracting data from, 80–81

Hypergeometric distribution, 185–186

Hypothesis tests in t-tests, 201–203

I

IDEs (Integrated Development Environments), 13–14

if else statements, 105–108

Images in LATEX documents, 360

@import tag, 382

Imports field for packages, 375

include option for knitr chunks, 365

Indenting code, 99

Independent variables in simple linear regression, 211

Indexes

arrays, 71

data.table, 129

LATEX documents, 360

lists, 66

Indicator variables

data.frame, 60

Elastic Net, 273, 289–290

multiple regression, 225

PAM, 345

Inferences

ensemble methods, 312

multiple regression, 216

@inheritParams tag, 382

Innovation distribution, 330

Input variables in simple linear regression, 211

inst folder, 373–374

Install dependencies option, 30

install.packages command, 31

Install Packages option, 30

installing packages, 29–32, 383–384

installing R, 2

on Linux, 10

on Mac OS X, 8–10

on Windows, 2–7

integer type, 38–39

Integers in regular expressions, 166

Integrated Development

Environments (IDEs), 13–14

Intel Matrix Kernel Library, 10

Interactivity, 13

Intercepts

multiple regression, 216

simple linear regression, 212–213

Interquartile Range (IQR), 85–86

Introduction to R, 394

Inverse gaussian linear model, 240

IQR (Interquartile Range), 85–86

Italics in Markdown, 367

Iteration with loops, 113

controlling, 115–116

for, 113–115

while, 115

J

Joining strings, 155–156

Joins, 142–143

data.table, 149

merge, 143–144

plyr package, 144–149

Joint Statistical Meetings, 393

K

k-fold cross-validation, 257–258

K-means algorithm, 337–345

K-medoids, 345–352

key columns with join, 144

keys for data.table package, 133–135

knots for splines, 302

L

L1 penalty, 271

L2 penalty, 271

Lags in autoregressive moving average, 318–319

lambda functions, 279–282, 285–289

Language selection, 3

lasso in Elastic Net, 271, 276, 279, 282

LATEX program

installing, 359

knitr, 362–367

overview, 360–362

Leave-one-out cross-validation, 258

Legends in scatterplots, 89

Length

characters, 40

lists, 66–67

vectors, 45–46

Less than symbols (<)

if and else, 105

variable assignment, 36

letters vector, 70

LETTERS vector, 70

Levels

Elastic Net, 273

factors, 48, 60

LICENSE file, 380

Licenses

Mac, 8–9

packages, 373–375

SAS, 77

Windows, 3

Line breaks in Markdown, 367

Line graphs, 94–96

Linear models, 211

generalized, 233–240

multiple regression, 216–232

simple linear regression, 211–216

LinkingTo field, 386

Links

C++ libraries, 386

hierarchical clustering, 352, 355

linear models, 240

Markdown, 368

Linux

C++ compilers, 385

downloading R, 1–2

installation on, 10

Lists

data.table package, 136–138

joins, 145–149

lapply and sapply, 118–119

Markdown, 367

overview, 61–68

Loading

packages, 32–33

rdata files, 162

log-likelihood in AIC model, 255

Log-normal distribution, 185–186

logical data type, 41–43

Logical operators

compound tests, 111–112

vectors, 46

Logistic distribution, 185–186

Logistic regression, 233–237

Loops, 113

controlling, 115–116

for, 113–115

while, 115

M

Mac

C++ compilers, 385

downloading R, 1

installation on, 8–10

Machine learning, 304

Machine Learning for Hackers, 394

Machine Learning meetups, 391

Maintainer field for packages, 375

makeCluster function, 283

makeindex, 360

Makevars file, 386–389

Makevars.win file, 386–389

man folder, 373–374

MapReduce paradigm, 117

Maps

heatmaps, 193

PAM, 350–351

Markdown tool, 367–369

Math, 35–36

Matrices

with apply, 117–118

with cor, 192

Elastic Net, 272

overview, 68–71

VAR, 324

Matrix Kernel Library (MKL), 10

.md files, 369–371

Mean

ANOVA, 209

bootstrap, 262

calculating, 187–188

normal distribution, 171

Poisson regression, 237–238

t-tests, 203, 205

various statistical distributions, 185–186

Mean squared error in cross-validation, 258

Measured variables in simple linear regression, 211

Meetups, 391–392

Memory in 64-bit versions, 2

Merging

data.frame, 143–144

data.table, 149

Minitab format, 77

Minus signs (-) in variable assignment, 36–37

Missing data, 50

apply, 118

cor, 195–196

cov, 199

mean, 188

NA, 50

NULL, 51

PAM, 346

MKL (Matrix Kernel Library), 10

Model diagnostics, 247

bootstrap, 262–265

comparing models, 253–257

cross-validation, 257–262

residuals, 247–253

stepwise variable selection, 265–269

Moving average (MA) model, 315

Moving averages, autoregressive, 315–322

Multicollinearity in Elastic Net, 273

Multidimensional scaling in K-means algorithm, 339

Multinomial distribution, 185–186

Multinomial regression, 240

Multiple group comparisons, 207–210

Multiple imputation, 50

Multiple regression, 216–232

Multiple time series in VAR, 322–327

Multiplication

matrices, 69–71

order of operation, 36

vectors, 44–45

Multivariate time series in VAR, 322

N

na.or.complete option, 196

na.rm argument

cor, 195–196

mean, 188

standard deviation, 189

NA value

with mean, 188

overview, 50

Name-value pairs for lists, 64

Names

arguments, 49, 100

data.frame columns, 58

directories, 18

lists, 63–64

packages, 384

variables, 37–38

vectors, 47

names function for data.frame, 54–55

NAMESPACE file, 377–379

Natural cubic splines, 302

Negative binomial distribution, 185–186

Nested indexing of list elements, 66

NEWS file, 379

Nodes in decision trees, 311–312

Noise

autoregressive moving average, 315

VAR, 324

Nonlinear models, 297

decision trees, 310–312

generalized additive model, 304–310

nonlinear least squares model, 297–299

random forests, 312–313

splines, 300–304

Nonparametric Ansari-Bradley test, 204

Normal distribution, 171–176

Not equal symbols (!=) with if and else, 105

nstart argument, 339

Null hypotheses

one-sample t-tests, 201–202

paired two-sample t-tests, 207

NULL value, 50–51

Numbers in regular expressions, 165–169

numeric data, 38–39

O

Objects, functions assigned to, 99

Octave format, 77

1/mu^2 function, 240

One-sample t-tests, 200–203

Operations

order, 36

vectors, 44–48

Or operators in compound tests, 111–112

Order of operations, 36

Ordered factors, 48

out.width option, 365

Outcome variables in simple linear regression, 211

Outliers in boxplots, 86

Overdispersion in Poisson regression, 238

Overfitting, 312

P

p-values

ANOVA, 208

multiple regression, 225

t-tests, 200–203

Package field in DESCRIPTION file, 374–377

Packages, 29, 373

building, 33

C++ code, 384–390

checking and building, 383–384

compiling, 387–390

DESCRIPTION file, 374–377

documentation, 380–383

files overview, 373–374

folder structure, 373

installing, 29–32, 383–384

loading, 32–33

miscellaneous files, 379–380

NAMESPACE file, 377–379

options, 23

submitting to CRAN, 384

uninstalling, 32

unloading, 33

Packages pane, 29–30

Paired two-sample t-tests, 206–207

pairwise.complete option, 197

PAM (Partitioning Around Medoids), 345–352

pandoc utility, 369–371

Pane Layout options, 21–22

Parallel computing, 282–284

@param tag, 381–382

Parentheses ()

arguments, 100

compound tests, 111

expressions, 63

functions, 99

if and else, 105

order of operation, 36

regular expressions, 163

Partial autocorrelation, 318–319

Partitioning Around Medoids (PAM), 345–352

Passwords in installation, 9

Patterns, searching for, 161–169

PDF files, 362, 369

Percent symbol (%) in pandoc, 369

Periods (.)

uses, 99

variable names, 37

Plots

coefficient. See Coefficient plots

faceted, 89–92

Q-Q, 249, 252

residuals, 250–251

scatterplots. See Scatterplots

silhouette, 346–348

Plus signs (+) in regular expressions, 169

Poisson distribution, 182–184

Poisson regression, 237–240

POSIXct data type, 40

Pound symbols (#)

comments, 46

Markdown, 368

package documentation, 381

pandoc, 369

Prediction in GARCH models, 335

Predictive Analytics meetups, 391

Predictors

decision trees, 310–311

Elastic Net, 272

generalized additive models, 304

logistic regression, 233

multiple regression, 216–217

simple linear regression, 211, 213

splines, 302–303

Priors, 290, 293–294

Probability distributions, 171

binomial, 176–181

miscellaneous, 185–186

normal, 171–176

Poisson, 182–184

Program FilesR directory, 4

Projects in RStudio, 16–19

prompt option for knitr chunks, 365

Q

Q-Q plots, 249, 252

Quantiles

binomial distribution, 181

multiple regression, 225

normal distribution, 175–176

summary function, 190

Quasibinomial linear model, 240

Quasipoisson family, 239

Question marks (?)

with functions, 49

regular expressions, 169

Quotes (”) in CSV files, 74

R

R-Bloggers site, 393

R CMD commands, 383

R Enthusiasts site, 393

R folder, 373–374

R in Finance conference, 393

R Inferno, 394

R Productivity Environment (RPE), 26–27

Raise to power function, 45

Random numbers

binomial distribution, 176

normal distribution, 171–172

Random starts in K-means algorithm, 339

Rcmdr interface, 14

.Rd files, 380, 383

RData files

creating, 77

loading, 162

Readability of functions, 99

Reading data, 73

binary files, 77–79

CSVs, 73–74

from databases, 75–76

Excel, 74–75

included with R, 79–80

from statistical tools, 77

README files, 380

Real-life resources, 391

books, 394

conferences, 393

documents, 394

meetups, 391–392

Stack Overflow, 392

Twitter, 393

Web sites, 393

Reference Classes system, 377

Registering clusters, 283

Regression

generalized additive models, 304

logistic, 233–237

multiple, 216–232

Poisson, 237–240

simple linear, 211–216

survival analysis, 240–245

Regression to the mean, 211

Regression trees, 310

Regular expressions, 161–169

Regularization and shrinkage, 271

Bayesian shrinkage, 290–294

Elastic Net, 271–290

Relationships

correlation and covariance, 191–200

multiple regression, 216–232

simple linear regression, 211–216

Removing variables, 37–38

Repeating command line commands, 15

Reshaping data, 141

cbind and rbind, 141–142

joins, 142–149

reshape2 package, 149–153

Residual standard error in least squares model, 298

Residual sum of squares (RSS), 254–255

Residuals, 247–253

Resources. See Real-life resources

Responses

decision trees, 310

logistic regression, 233

multiple regression, 216–217, 219, 225

Poisson regression, 237

residuals, 247

simple linear regression, 211–213

@return tag, 381–382

Return values in functions, 103

Revolution Analytics site, 393

Ridge in Elastic Net, 271, 279

.Rmd files, 369

.Rnw files, 362

Rows

in arrays, 71

bootstrap, 262

cbind and rbind, 141–142

data.frame, 53

data.table, 131

with mapply, 120

matrices, 68–70

RPE (R Productivity Environment), 26–27

RSS (residual sum of squares), 254–255

RStudio overview, 15–16

Git integration, 25–26

projects, 16–19

tools, 20–25

RTools, 385

Run as Administrator option, 3

Running code in parallel, 283

S

S3 system, 377

@S3method tag, 382

S4 system, 377

s5 slide show format, 369

SAS format, 77

Scatterplots, 84–85

correlation, 192

generalized additive models, 307

ggplot2, 88–91

multiple regression, 220–224

splines, 303

scope argument, 265

Scraping web data, 81

Seamless R and C++ Integration with Rcpp, 394

Searches, regular expressions for, 161–169

Secret weapon, 293

Sections in LATEX documents, 361

@seealso tag, 382

Seeds for K-means algorithm, 338

Semicolons (;) for functions, 100

sep argument, 155

Shapefile objects, converting into

data.frame, 349

Shapiro-Wilk normality test, 204

Shortcuts, keyboard, 15

Shrinkage

Bayesian, 290–294

Elastic Net, 271

Silhouette plots, 346–348

Simple linear regression

ANOVA alternative, 214–216

overview, 211–214

Single linkage methods, 352, 355

64-bit vs. 32-bit R, 2

Size

binomial distributions, 176–179

lists, 65

sample, 187

Slashes (/) in C++ code, 385–386

Slide show formats, 369

slideous slide show format, 369

slidy format, 369, 371

Slope in simple linear regression, 212–213

Small multiples, 89

Smoothing functions in GAM, 304

Smoothing splines, 300–301

Software license, 3

Spelling options, 23–24

Splines, 300–304

Split-apply-combine method, 117, 124

SPSS format, 77

Square brackets ([])

arrays, 71

data.frame, 56, 58

lists, 65

Markdown, 368

vectors, 47

Squared error loss in nonlinear least squares model, 297

src folder, 373–374, 387

Stack Overflow source, 392

Standard deviation

missing data, 189

normal distribution, 171

simple linear regression, 213

t-tests, 201–202, 205

Standard error

Elastic Net, 279, 289

least squares model, 298

multiple regression, 225–226

simple linear regression, 213–216

t-tests, 202

start menu shortcuts, 6

startup options, 5

Stata format, 77

Stationarity, 318

Statistical graphics, 83

base, 83–86

ggplot2, 86–97

Statistical tools, reading data from, 77

Stepwise variable selection, 265–269

Strings, 155

joining, 155–156

regular expressions, 161–169

sprintf, 156–157

text extraction, 157–161

stringsAsFactors argument, 75

Submitting packages to CRAN, 384

Subtraction

matrices, 68

order of operation, 36

vectors, 44–45

Suggests field in packages, 375–376

Summary statistics, 187–191

Survival analysis, 240–245

SVN repository, 17, 19, 25

switch statements, 108–109

Systat format, 77

T

t distribution

functions and formulas, 185–186

GARCH models, 330

t-statistic, 201–202, 225

t-tests, 200

multiple regression, 225

one-sample, 200–203

paired two-sample, 206–207

two-sample, 203–206

Tab key for autocompleting code, 15

Tables of contents in pandoc, 371

Tags for roxygen2, 381–382

Tensor products, 308

test folder, 374

Text

extracting, 157–161

LATEX documents, 362

regular expressions, 167–169

Themes in ggplot2, 96–97

32-bit vs. 64-bit R, 2

Tildes (∼) in aggregation, 120

Time series and autocorrelation, 315

autoregressive moving average, 315–322

GARCH models, 327–336

VAR, 322–327

Title field, 374–375

@title tag, 382

Titles

help files, 381

LATEX documents, 360

packages, 374–375

slides, 369

Transposing matrices, 70

Trees

decision, 310–312

hierarchical clustering, 354

TRUE value

with if and else, 105–108

with logical operators, 41–43

Twitter resource, 393

Two-sample t-tests, 203–206

Type field for packages, 374–375

Types. See Data types

U

Underscores (_)

Markdown, 367

variable names, 37

Unequal length vectors, 46

Uniform (Continuous) distribution, 185–186

Uninstalling packages, 32

Unloading packages, 33

@useDynLib tag, 382

useful package, 273, 341

UseMethod command, 377

useR! conference, 393

User installation options, 9

V

VAR (vector autoregressive) model, 322–327

Variables, 36

assigning, 36–37

names, 37

relationships between, 211–216

removing, 37–38

stepwise selection, 265–269

Variance, 189

ANOVA, 207–210

GARCH models, 327

Poisson regression, 238

t-tests, 203

various statistical distributions, 185–186

Vector autoregressive (VAR) model, 322–327

Vectorized arguments with ifelse, 110

Vectors, 43–44

data.frame, 56

factors, 48

in for loops, 113–114

multiple regression, 217

multiplication, 44–45

operations, 44–48

paste, 155–156

sprintf, 157

Version control, 19

Version field for packages, 375

version number, saving, 6–7

Versions, 2

Vertical lines (|) in compound tests, 111

vim mode, 21

Violins plots, 91–94

Volatility in GARCH models, 330

W

Weakly informative priors, 290

Websites

extracting data from, 80–81

R resources, 393

Weibull distribution, 185–186

Welch two-sample t-tests, 203

while loops, 115

White noise

autoregressive moving average, 315

VAR, 324

WiFi hotspot locations, 297–298

Windows

C++ compilers, 385

downloading R, 1

installation on, 2–7

Windows Live Writer, 15

within-cluster dissimilarity, 343

Wrapper functions, 386

Writing R Extensions, 394

X

X-axes in nonlinear least squares model, 298

Xcode, 385

Y

Y-axes in nonlinear least squares model, 298

y-intercepts

multiple regression, 216

simple linear regression, 212–213

Z

Zero Intelligence Agents site, 393

zypper mechanism, 2