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Krause A., Olson M. — The basics of S-plus |
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Предметный указатель |
Graph, omitting axes 128
Graph, orientation 122
Graph, plot character 126
Graph, plot region 132
Graph, size 133
Graph, subtitle 126
Graph, surrounding box 126
Graph, title 126
Graph, type 126
Graphical User Interface see “GUI”
Graphics 119—145
Graphics devices 120
Graphics devices, active 120
Graphics devices, closing 121 152
Graphics devices, closing all 121 152
Graphics devices, multiple 122
Graphics devices, options 122
Graphics options see “par”
Graphics plot options 124—125
Graphics plotting data 122—125
Graphics settings, storing and restoring 364
Graphics type option 124
Graphics window 121 151
graphics.off 123
graphs see “Graph”
graphsheet 119 120 151 304 376
greater than (>) 83
greater than or equal to (>=) 83
Greek letters in graphs 385
Green book 2
GUI 7
help 73 111 112 114
help system 18—19 72 73
hexbin 206
hist 147 206 225 240
hist2d 186 187 199 200 203
histogram 147 149 150 190 226
history 365
History of S and S-Plus 2—4
hpgl 121
Hypergeometric distribution 208
Hypothesis testing 212
i 211 246 372
Identical 316
Identify 206
Image 200 206
importdata 335—337 344 345 372
importing data 336—340
Importing data via GUI 11 22—23
Index variables 86 246
Indicator variables 86 246
inf 220 227 380
Infinite values see “Inf”
Insightful Corp. 3
INSPECT 299
interaction.plot 256 269
Interactive 299
iris4d 121
is.factor 247
is.finite 220
is.inf 220
is.na 107 113 218 220 231
is.numeric 359
Iteration 289—294
java.graph 151
Kaplan — Meier 251
Key 164 166 169 170 172 210
kruskal.test 215
ks.gof 215
ksmooth 243
Kyphosis data set 249 254
labels 247
Landscape mode see “Graph orientation”
lapply 186 276—277 331 332
Last expression’s output see “.Last.value”
LATEX 381 384—385
Lazy evaluation 285
Length 87 90 91 375
less than (<) 83
Less than or equal to (<=) 83
letters 175
Leukemia data set 251
levelplot 149 202
Levels see “Factor” 369
Levels of calls 355
Libraries 380—381
Library 380
lines 128 220 240 244
Linking C and Fortran programs 376
Linux GUI 45—54
Lissajous figures 138 144 303 304
LIST 95 96 104 105 115 248
LISTS 93 104—106 271—280
Lists, adding elements 273
Lists, applying a function to all elements see “lapply”
Lists, create empty 274
Lists, deleting elements 273
Lists, exercise 303 306
Lists, names of elements 274
Lists, referencing elements 105
Lists, syntax 104
Lists, unlisting 280
LM 219 238 241—243 248 249 258
lme 256 270
local variables 104
LOESS 166 241 242
Logical comparisons 83
Logical comparisons, equal to 83 109
Logical comparisons, example of 90
Logical comparisons, greater than 109 246
Logical comparisons, less than 109
Logical comparisons, not 83 107
Logical comparisons, not equal to 83
Logical values 83—85
Logistic distribution 208
Logistic regression 249—251 254
Lognormal distribution 208
Loops see “Iteration”
LOWESS 240
macros 2
make.groups 163 166
Manova 241 242 255
mantelhaen.test 215
MAP 381
Match 170 171 328
Mathematical operations 80—81
MathSoft 2
matplot 206
Matrices 93—99
Matrices, addition 97
Matrices, assigning elements 97
Matrices, defining dimensions 94
Matrices, inverse of 98
Matrices, merging 99 110
Matrices, multiplication 98
Matrices, naming rows and columns 95
Matrices, overwriting elements 97
Matrices, referencing entries 82 96
Matrices, singular value decomposition 98
Matrices, subtraction 97
Matrices, syntax 94
Matrix 94 95 340
MAX 91 102 107 113 114 229
mcnemar.test 215
Mean 87 107 186 219 279
Median 186 219
MERGE 108
merging data 108
Merging matrices see “Matrices merging”
mfrow 240 246
| MIN 229
missing 287
Missing values see “NA”
Model building 239 244—247
Model diagnostics 239—241 246
Model syntax 242—243
Motif 119—121
ms 241
Mtext 227
Na 106—107 113 128 169 217—221 227
na.exclude 219
na.fail 219
na.rm 113 114
Names 106 228 274 374
NaN 380
Negative binomial distribution 208
NEW 311—313
Newline character in strings 300
NeXT 291
NLS 241
nls, ms 242
No room for x axis (error message) 135
Normal distribution 208
Normal distribution, multivariate 208
Not equal to (!=) 83
Notational conventions 6
NULL 273 274
Object Explorer 9 16—18
Object Explorer, object classifications 16
Object Explorer, toolbar 16
Objects 76 329 331
Objects summary window 46
Old S 2
on.exit 364 393
openData 372
openlook 121
Operating systems 4—5
Options echo 296
Options error 299
options setting see “par”
Options warn 296
Order 110 114
order of operations 74
ordered 247 255 389
Ordered factor see “Factor ordered”
Outer 303 304
Output device see “Graphics device”
Overparameterization see “Regression overparameterization”
Overwriting S-Plus objects 76
Pairs 206
Panel function 172
panel.barchart 174
panel.lmline 171
panel.loess 171
panel.superpose 162
panel.xyplot 171
PAR 131 133 240
parallel 149
Parameters, adding self-defined 132
Parentheses see “Brackets round”
parse 329 347
Paste 301 302 347 369
PDF files see “Acrobat reader”
Permanency of S-Plus objects 76
persp 200 206 303 305
PI 91
Pi, estimation of 223 233
Picture see “Graph”
pie 206
PieChart 149
plot 123 127 206 211 220 240 243 244 246 310
plot.design 256 269
plot.gam 254 263
plot.glm 263
Plotting dashed lines 220
POINTS 128
Pointwise 246
Poisson distribution 208
POLY 246
poly.transform 246
Polygon 174 217
Portrait mode see “Graph orientation”
PostScript 122 151
PostScript, Encapsulated 382 383
Power, raising to a 74 89 90
PowerPoint 41
Predict 246
princomp 241 242
print 76 150
print.default 368
Printer see “Graphics”
Printing see “Graphics”
Probability function 207
Probability inverse see “quantile”
Programming 271—307
Programming, exercises 303—307
Prompt changing 365
prop.test 215
ps.options 134
Psfrag utility 386
q 72
QPE 2
qq 149
qqline 241
qqmath 149
qqnorm 241
QT 217
Quantile 182 183 186 257
Quitting S-Plus 72
R 3 399—402
R-squared 239
random number generation 207
rapply 278—279
rbind 99 110
read.table 335 338 339 372
reading data 335 340—341
readline 340
Record 335 343
Recover 299 300 319
Rectangle, plotting a 138 141
Referencing entries 82
Regression diagnostics see “Model diagnostics”
Regression, adding terms 244
Regression, coding of variables 259
Regression, confidence intervals 246
Regression, example 237—239
Regression, factor variables 246—247
Regression, intercept 239 258
Regression, logistic see “Logistic regression”
Regression, model output 239 244
Regression, overparameterization 258
Regression, polynomial 246 248
Regression, predicted values 246
Regression, simple linear 241 244—247
Regression, standard errors 246
Regression, stepwise see “Stepwise regression”
Remove 363
Removing S-Plus objects see “rm”
rep 79 81 86 264
REPEAT 291
REPLICATE see “rep”
resid 240 241
Residual analysis see “Model diagnostics”
Residuals 239
restore 342
RETURN 106 282 284 347
rev 114
rm 76 103
round 89 92 113 188 347
Roundoff error 89
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