learnR.ind

\begin{theindex}

  \item analysis issues
    \subitem analysis of summary data, 73, 100
    \subitem assumptions, 44, 48, 150, 153, 156, 158--160, 170, 180, 
		183, 186, 192, 197, 198, 204
    \subitem deficiencies, 47
    \subitem independence, 48, 150, 159
    \subitem nonparametric methods, 195, 198
    \subitem robust \& resistant methods, 45, 48, 183, 198
    \subitem source/target differences, 243
    \subitem styles of analysis, 59, 187, 233
  \item analysis of variance model (aov)
    \subitem one-way layout, 164
  \item argument, \see {function}{}
  \item array
    \subitem dimensions, 67, 70, 76, 84, 100, 101, 104
  \item assignment, 21, 40, 146, 199

  \indexspace

  \item Bayesian methods, 44
    \subitem prior density or probability, 44, 197
  \item bootstrap, \see {resampling methods}{}
  \item boxplot, \see {graphics, box \& whisker}{}

  \indexspace

  \item classes \& methods, 80--82, 195, 202, 210, 218--220
    \subitem S4, 195
  \item commands
    \subitem comment character, 13, 15, 35, 88, 92
    \subitem continuation character, 13
  \item concatenation, 65
  \item confidence interval (CI), 2, 6--8, 12--24, 28, 29, 31--34, 36, 
		38--41, 44--56, 58, 60, 62--65, 67, 68, 70--80, 82, 
		84, 85, 88, 89, 92, 93, 95, 97, 100, 101, 103, 104, 
		107, 111, 112, 116--122, 127, 129, 130, 132, 133, 
		136, 137, 140--143, 145, 147, 148, 150--162, 164--168, 
		170--179, 181--184, 186--188, 190, 193--195, 197--200, 
		202, 204--206, 208--210, 212, 214, 216--218, 220, 222, 
		224, 225, 232--234, 237, 238, 241, 243
    \subitem median
      \subsubitem bootstrap, 172
    \subitem predicted values, 53, 152, 158, 183, 197
  \item contrasts, \see {factor}{}
  \item correlation
    \subitem linear (Pearson), 50, 51, 57, 159, 168, 188
  \item cross-validation see {resampling methods}, 1

  \indexspace

  \item data
    \subitem input, 29, 88, 89, 91, 93, 95, 97
      \subsubitem comment character, 15, 88, 89, 92
    \subitem management strategies, 39, 101, 103, 105, 107, 109--111, 
		113
    \subitem measurement issues, 48, 82, 126, 133, 182, 183, 195, 202
    \subitem summary, 73, 100
  \item data analysis \& commentary
    \subitem alcohol consumed, by year \& country ({\tt grog}), 
		128, 129, 145
    \subitem Antiguan corn yields ({\tt ant111b}), 86, 186
    \subitem Australian athletes, morphology \& biochemistry ({\tt ais}), 
		126, 138, 139
    \subitem book weight vs dimensions ({\tt allbacks}, {\tt softbacks}), 
		86
    \subitem book weight vs dimensions, biased sample ({\tt oddbooks}), 
		184
    \subitem Canadian city populations ({\tt cities}), 202, 204
    \subitem car data
      \subsubitem fuel consumption, etc, 1974 data ({\tt mtcar} {\itshape datasets}), 
		214, 215
      \subsubitem speed vs distance to stop ({\tt cars}, {\itshape datasets}), 
		214, 215
    \subitem cricketer survival rates ({cricketer}), 107, 108
    \subitem depression vs lawn roller weight ({\tt roller}), 151, 152
    \subitem elastic bands, distance vs stretch ({\tt elastic1}, {\tt elastic2}, {\tt elasticband}), 
		83, 116, 184
    \subitem height \& weight of women ({\tt women}, {\itshape datasets}), 
		40, 47, 116
    \subitem hill race times ({\tt nihills}, {\tt hills2000}), 24, 
		55--57, 96, 143, 144, 154, 155, 157--159, 167--169, 
		184
    \subitem human power vs O$_2$ intake ({\tt humanpower1}, {\tt humanpower2}), 
		218, 219
    \subitem hurricane death data ({\tt hurricNamed}), 195
    \subitem jobs, by region of Canada ({\tt jobs}), 79, 131, 132
    \subitem population growth
      \subsubitem Australian states ({\tt austpop}), 116, 126
    \subitem pressure of mercury vapour, vs temp ({\tt pressure}, {\itshape datasets}), 
		45, 243
    \subitem primate body \& brain weights ({\tt primates}), 117, 
		125, 126, 134, 135
    \subitem track \& road record times ({worldRecords}), 51--55, 60
    \subitem tree dimensions \& biomass ({\tt rainforest}), 40, 41
    \subitem UCB admissions, by sex \& dept ({\tt UCBAdmissions}, datasets), 
		74, 76, 100--103, 106
  \item data frame, 1
    \subitem as database, 96
    \subitem as list, 15, 20, 23, 56, 62, 67, 68, 70, 71, 76, 79--84, 
		100, 104, 105, 146, 148, 196, 214
    \subitem attach \& detach, 20, 24, 29, 50, 83
    \subitem column \& row names, 101, 105
    \subitem convert to/from tables or matrices, 101
    \subitem joining (cbind, rbind), 68
    \subitem omit rows with NAs, 69, 70, 81
    \subitem reshape, 73, 104, 105, 108, 109
    \subitem split to list, 77, 80, 81, 106, 107, 198
    \subitem writing, 23, 36, 77, 84, 85, 88, 105, 109, 137, 163, 196, 
		198
  \item data mining, 229
  \item degrees of freedom, 55, 179
  \item density
    \subitem estimate, 50, 122, 138
      \subsubitem plot, {\itshape} plot, 1
  \item designed experiment, 6, 47
  \item deviance, \see {model}{}
  \item discriminant analysis
    \subitem linear, 67, 195, 196, 201
  \item distance measure, 202, 203
  \item distribution
    \subitem $t$-distribution, 170
      \subsubitem degrees of freedom, 170
    \subitem betabinomial, 49
    \subitem binomial, 49, 178
    \subitem cumulative probability, 121
    \subitem density, 50, 121, 122, 138, 139, 147, 148, 178
    \subitem exponential, 49
    \subitem normal, 40, 48, 49, 121--123, 147, 148, 153, 154, 157, 158, 
		197
    \subitem Poisson, 194
    \subitem sampling distribution, 48, 154
    \subitem skew, 50, 51, 57, 154, 174, 178
    \subitem uniform, 147, 148
  \item document preparation
    \subitem Sweave, 34, 38, 39

  \indexspace

  \item exploratory data analysis (EDA), 28, 80, 83, 92, 106, 120, 157, 
		177, 180
  \item expression
    \subitem evaluate, 23, 124, 216, 234

  \indexspace

  \item factor, 62, 64, 65, 69, 83, 84, 88, 108, 110, 127, 130, 
		162, 163, 166, 198, 210
    \subitem columns in model matrix, 165
    \subitem contrasts, 166
    \subitem in model formula, 150, 151
    \subitem levels, 83, 108, 162
      \subsubitem order, 83, 108, 162
    \subitem ordered, 65
    \subitem splitting by levels, 171, 198
  \item file names, 13, 14, 19--21, 23, 24, 28--31, 35--37, 39, 40, 68, 
		75, 76, 88, 89, 92--94, 97, 109, 110, 144, 208, 
		210, 211, 217, 223, 226
  \item fixed effects, \see {multi-level model}{}
  \item function, 12, 23, 28, 39, 56, 57, 62, 64, 65, 68, 72, 82, 83, 
		89, 90, 96, 97, 107, 109, 116, 124, 126--128, 130, 
		133--138, 141, 143, 146, 147, 171, 181, 194, 204, 
		209--211, 216, 217, 225, 228, 241
    \subitem anonymous, 75, 77
    \subitem argument, 135
      \subsubitem abbreviated, 78
      \subsubitem pass via list, 135
      \subsubitem the \texttt{\ldots} argument, 18
    \subitem common useful functions, 20, 21, 44, 49, 50, 54, 55, 57, 
		62, 66--68, 71, 80, 82, 84, 104, 117, 150, 156, 174, 
		182, 187, 192, 193, 202, 203, 209, 210, 220, 234, 241
    \subitem environment, 31, 39, 41, 210, 216, 219, 220, 226, 233
      \subsubitem evaluation frame, 29, 41, 210, 216
    \subitem generic, 44, 54, 55, 81--84, 201, 218
    \subitem issues for writing \& use, 44, 49, 57, 62, 100, 146, 161, 
		181, 182, 194, 209, 234
    \subitem return value, 40, 66, 67, 71, 72, 75, 76, 80, 82, 83, 86, 
		90, 100, 104--106, 125--127, 136, 146, 150, 152, 156, 
		210, 217
    \subitem utility functions, 110

  \indexspace

  \item generalized linear model, \seealso{regression}{}
    \subitem deviance, 179, 197
      \subsubitem deviance residuals, 179, 197
    \subitem family, 178, 179
      \subsubitem betabinomial, 178, 179
      \subsubitem binomial, 178, 179
      \subsubitem poisson, 178, 179
      \subsubitem quasibinomial, 178, 179
      \subsubitem quasipoisson, 178, 179
    \subitem linear predictor, 171, 179, 197
    \subitem logistic regression, 197
    \subitem predicted values,
      \subsubitem linear predictor, 197
      \subsubitem response, 197
    \subitem residuals
      \subsubitem working, 156, 161
    \subitem SEs \& Wald ($z-$) statistics for coefficients, 171, 197
      \subsubitem Hauck-Donner effect, 171, 197
  \item ggplot2 graphics, 3, 31, 57, 115--117, 119, 121, 123--125, 127, 
		129, 131, 133, 135--139, 141--143, 145--147, 241
    \subitem use of quickplot(), 57, 136--141
  \item graph
    \subitem {\itshape see} plot, 1
  \item graphics, \seealso{ggplot2, lattice}{}
    \subitem aspect ratio, 52, 120, 125, 127, 132, 146, 196, 201, 234
    \subitem box-\&-whisker
      \subsubitem outlier criterion, 140
    \subitem contour, 125, 138--140, 157, 178, 181
    \subitem dates as axis labels, 79, 132
    \subitem devices, 52, 117, 121, 126--128, 131, 217
    \subitem histogram, 121, 122, 133, 136, 138, 147
    \subitem simulated data, 160, 161
    \subitem transformation of scales, 44, 49, 50, 121, 156, 178, 204
  \item graphics (base graphics)
    \subitem axes, 19, 50--52, 119, 130, 131, 136, 137, 139, 142, 145, 
		204, 214
    \subitem identifying points, 51, 88, 144
    \subitem interaction plot, 58, 59, 150, 154, 170, 174, 201
    \subitem legend, 119, 130, 178
    \subitem normal probability, 121--123, 147
    \subitem panel function, 56, 133--135
    \subitem shaded regions, 191
    \subitem size of points \& text, 18, 19, 50, 51, 59, 117--120, 127, 
		135, 137, 157, 164, 178, 192, 210, 211

  \indexspace

  \item image file, \see {R session}{}
  \item inference, 46--48, 100
    \subitem bootstrap methods, \see {resampling methods}{}
    \subitem confidence interval, \see {confidence interval}{}
  \item information criteria
    \subitem Akaike Information Criterion (AIC), 177, 179

  \indexspace

  \item lattice graphics, 3, 24, 31, 52, 56, 64, 73, 79, 82, 115--117, 
		119, 121, 123--127, 129--133, 135--137, 139, 141--143, 
		145--148, 168, 186, 196, 228, 234
    \subitem add smooth curve, 117, 119, 129, 137, 141, 186
    \subitem adding to plots, 31, 125, 133, 135, 147
    \subitem box plot, 142
    \subitem built on grid package, 116, 125, 130, 136, 139
    \subitem conditioning factor or variable, 127, 139, 228
    \subitem dotplot, 73, 132
    \subitem keys \& legends, 52, 117, 119, 127, 129, 130, 133, 135, 
		137, 148, 196
    \subitem layout of panels, 56, 121, 125, 126, 131, 147
    \subitem panel function, 56, 133, 135
    \subitem point \& text size, 52, 82, 116, 117, 119, 121, 123, 124, 
		126, 127, 129--131, 135, 137, 141, 143, 145, 147, 148, 
		168
    \subitem printing from user functions, 124, 126
    \subitem scaling of axes, 24, 52, 79, 82, 127, 130, 131, 135--137, 
		139, 145, 148, 168, 186, 196
    \subitem strip plot, 130, 142, 148, 186
  \item library, \seealso{package}{}, 7, 28, 30, 32, 125, 196, 210, 
		218, 228, 237
  \item linear model (lm), 71, 150, 162, 171, 180, 234
    \subitem assumptions, 180
    \subitem bootstrap, \see {resampling methods}{}
    \subitem check for linearity, 171, 180
    \subitem confusion between $x$ \& $y$, 182
    \subitem cross-validation, \see {resampling methods}{}
    \subitem design, 234
    \subitem diagnostic plots
      \subsubitem residuals vs leverage, 150
    \subitem errors in $x$, \see {regression}{}
    \subitem explanatory variables
      \subsubitem relationships, 150, 162, 171
    \subitem fitted values, \see {predicted values}{}
    \subitem hat matrix, 71, 150, 162, 171, 180, 234
    \subitem model formula, 150, 151
    \subitem model matrix, 150
      \subsubitem one term; several columns, 150, 153, 163--165
    \subitem modeling non-linear responses, 51, 150, 201
    \subitem outliers, \see {regression, outliers}{}
    \subitem predicted values
      \subsubitem validity of SE estimates, 180
    \subitem prediction interval (new $y$-value), 150
    \subitem regression spline, \see {regression}{}
    \subitem residual SE
      \subsubitem degrees of freedom, 180
    \subitem residuals, \see {regression}{}
    \subitem robust \& resistant methods, \see {regression}{}
    \subitem straight line model, 150
      \subsubitem fitted values, 150
      \subsubitem residual, 150
    \subitem strategies for fitting models, \see {regression}{}
    \subitem term plots, 150, 163--165, 169, 175, 179
    \subitem terms, 150, 162, 171, 180, 234
    \subitem variable selection, 170, 171
      \subsubitem realistic SEs, 170, 171
      \subsubitem simulation, 170, 171
  \item list, 62, 100
  \item list, concatenate (join), 84

  \indexspace

  \item matrix, 44, 50, 56, 66--68, 70, 76, 84, 88, 100, 104, 112, 113, 
		150, 153, 168, 173, 195, 204, 210
    \subitem arithmetic, 112, 153
    \subitem conversion to/from data frame, 68, 209
    \subitem conversion to/from vector, 20, 67, 68, 70, 73, 76, 84, 100, 
		104, 153, 210
    \subitem joining (cbind, rbind), 68
    \subitem number of rows \& columns, 67, 70, 76, 84, 100, 104, 105, 
		195, 196, 200--202, 204
    \subitem storage in memory, 84
    \subitem subscripts, 20, 112, 210
  \item missing values, 40, 64, 66, 69, 72, 83, 84, 86, 90, 148
    \subitem count \& identify, 40, 64, 83
    \subitem remove, 66, 72
  \item model
    \subitem classification, \see {discriminant analysis}{}
    \subitem discriminant, \see {discriminant analysis}{}
    \subitem generalized linear model, 
		\see {regression, generalized linear model}{}
    \subitem linear model, \see {regression, linear model}{}
    \subitem model formula, 150, 151
    \subitem model object, 44, 53--55, 62, 71, 84, 100, 150, 152, 229
      \subsubitem extractor function, 44, 55
    \subitem parameters, 150, 161, 162, 165, 174
    \subitem survival analysis, \see {survival analysis}{}
    \subitem time series, \see {time series}{}
  \item multi-dimensional scaling (MDS), \see {ordination}{}
  \item multilevel model, 186, 187
  \item multivariate analysis, 187, 197

  \indexspace

  \item nonsense, 46

  \indexspace

  \item object
    \subitem saving, 12, 13, 23, 28--30, 39, 110, 111, 113, 136, 138, 
		152, 210
  \item operator, 16, 133, 137, 141, 218
    \subitem arithmetic, 16, 133, 137, 218
    \subitem relational, 16
  \item ordination
    \subitem distance measure, \see {distance measure}{}
    \subitem multi-dimensional scaling (MDS), 201, 205, 206
    \subitem principal components analysis (PCA), 67, 95, 204
      \subsubitem PCA scores in regression, 67

  \indexspace

  \item package
    \subitem base, 6, 10, 12, 14, 22, 25, 28, 30--32, 75, 78, 88, 
		93--96, 101, 104, 107, 116, 118, 125, 126, 133, 135, 
		141--143, 145, 147, 148, 150, 195, 198, 210, 217, 226, 
		228, 232--234
    \subitem boot, 150
    \subitem car, 6, 23, 40, 45, 88, 143, 225, 228
    \subitem cluster, 50, 203
    \subitem DAAG, 7, 21, 24, 30, 32, 40, 55, 73, 80, 89, 97, 103, 104, 
		108, 109, 116, 126, 133, 143, 145, 147, 161, 177, 179, 
		184, 186, 187, 191, 198, 208, 211, 223, 237
    \subitem datasets, 7, 19, 31, 40, 45, 50, 86, 104, 109, 112, 113, 
		116, 237
    \subitem dr, 15, 20, 34, 36, 45, 55, 88--90, 93, 94, 96, 105, 112, 
		125, 135, 143, 180, 186, 187, 195, 197, 222, 225, 228, 
		232--234
    \subitem foreign, 89
    \subitem gam, 180, 189, 191, 193
    \subitem ggplot2, 31, 57, 116, 125, 133, 135, 136, 141--143, 145, 
		147, 241
    \subitem grid, 116, 125, 136, 203, 219
    \subitem lme4, 82, 100, 187
    \subitem MASS, 31, 40, 45, 50, 195
    \subitem mgcv, 180, 189
    \subitem nlme, 187
    \subitem R Commander (Rcmdr), 15
    \subitem RColorBrewer, 118
    \subitem rpart, 198
    \subitem RSQLite, RMySQL, ROracle, DBI, 96
    \subitem stats, 22, 31, 206, 241
  \item plot, \see {graphics}{}
  \item posterior density or probability, \see {Bayesian methods}{}
  \item predictive accuracy, 
		\see {regression, generalized linear model, linear model (lm), model, survival analysis}{}
  \item principal components analysis (PCA), \see {ordination}{}
  \item printing, 12, 37, 77, 78, 124, 126, 216
    \subitem digits, 32, 78, 167, 196
  \item prior density or probability, \see {Bayesian methods}{}

  \indexspace

  \item quitting a session, 14, 28, 110

  \indexspace

  \item R session
    \subitem image file, 24, 28, 29, 31, 40, 110, 111, 113, 146
    \subitem quitting, 14, 28, 110
    \subitem search list, 28, 31, 39
      \subsubitem database, 20, 28, 31, 39, 217
    \subitem working directory, 7, 13, 14, 21, 24, 28, 29, 39, 40, 89, 
		96, 110, 222, 225, 237
      \subsubitem changing, 21
    \subitem workspace, 7, 11--14, 17, 19--21, 23, 24, 28, 29, 31, 39, 
		62, 83, 110, 111, 113, 146, 208, 210, 216, 225, 228, 
		237
      \subsubitem image, 12, 14, 20, 24, 28, 29, 31, 39, 110, 111, 113, 
		146, 210, 228
      \subsubitem management, 39, 110, 111, 113
  \item random
    \subitem numbers, 41
    \subitem sample, 44, 147, 199, 200
  \item regression, 
		\seealso{discriminant analysis, generalized additive model, tree-based methods, survival analysis, time series}{}
    \subitem AIC (Akaike), BIC (Bayesian), Cp (Mallows), 
		\see {information criteria}{}
    \subitem bootstrap, \see {resampling methods}{}
    \subitem coefficients
      \subsubitem confidence interval, \see {confidence interval}{}
      \subsubitem interpretation, 53, 162
      \subsubitem standard error, 55, 150, 170, 172
    \subitem comparison of models, 57, 154, 167, 187, 197, 233
    \subitem diagnostics, 44, 53, 60, 150, 156, 157, 160
    \subitem extrapolation, 159, 192
    \subitem generalized additive model, 
		\see {generalized additive model}{}
    \subitem generalized linear model, 
		\see {generalized linear model}{}
    \subitem linear model, \see {linear model}{}
    \subitem non-linear model, 150
    \subitem observational data, 46, 162
    \subitem outlier, 50, 158, 170, 184
    \subitem predictive accuracy
      \subsubitem bootstrap, 44
      \subsubitem cross-validation, 150
      \subsubitem validity of bootstrap estimate, 44
    \subitem residuals
      \subsubitem normal probability plots, 180
    \subitem spline smoother, \seealso{Generalized Additive Model}{}, 
		180
  \item replication, 46
  \item resampling methods
    \subitem bootstrap, 44, 150, 172, 199, 200
    \subitem cross-validation, 44, 150, 172, 196
  \item rounding, 18, 37

  \indexspace

  \item sampling
    \subitem cluster sampling, 48
    \subitem with/without replacement, 44
  \item search list, \see {R session}{}
  \item selection bias, 172
  \item simulation, 156, 160, 161, 171, 172, 182, 190, 191, 193
  \item smoother, 141, 150, 179, 180, 192
    \subitem Generalized Additive Model, 180, 192
    \subitem lowess, 179, 180
  \item spline, 117, 141, 150, 172, 180, 234
  \item standard deviation, 48, 75, 84--86, 202, 203
  \item standard error (SE), 16, 21, 37, 44, 55, 58, 62--64, 66, 68, 69, 
		72, 73, 77, 88, 92, 95, 119, 122, 128--131, 141, 142, 
		144, 150, 153, 170, 172--174, 176, 182, 184, 188, 192, 
		194, 196, 204, 208, 210, 211, 225, 226
    \subitem of mean (SEM), 170, 172, 182
    \subitem of median, 172
    \subitem of residual, 55, 170

  \indexspace

  \item table
    \subitem of frequencies
      \subsubitem table formula, 18, 64, 74, 104, 127, 152, 214, 220, 
		234
  \item test
    \subitem correlation, 59, 192
    \subitem F-statistic, 170
    \subitem homogeneity of variance, 48
    \subitem proportion(s), 52, 203
    \subitem sequential correlation, 216
    \subitem type III, 174
  \item time series, 92, 159, 183, 187, 188, 190, 191, 193
    \subitem ARMA or ARIMA model, 193
      \subsubitem automated selection, 193
    \subitem autocorrelation, 188--190, 192, 193
    \subitem autoregressive (AR) model, 2, 3, 6--25, 28--42, 44--60, 
		62--86, 88--97, 100--113, 116--184, 186--206, 208--212, 
		214--220, 222--226, 228, 229, 232--234, 237, 238, 
		240--243
    \subitem moving average (MA) model, 193
  \item transformation
    \subitem count data
      \subsubitem angular, 121, 203
    \subitem logarithmic, 49, 50, 156, 178, 203
    \subitem use of, 44, 46, 49, 50, 121, 156, 203, 204
  \item tree-based methods
    \subitem random forests (randomForest), 40, 41, 195, 197--201
    \subitem rpart
      \subsubitem classification, 195, 199--201
      \subsubitem error or impurity measures, 197
      \subsubitem information on each split, 198
      \subsubitem output, 198
      \subsubitem predictive accuracy, 201
      \subsubitem pruning, 199
      \subsubitem regression, 50, 182, 195, 199
      \subsubitem tree diagram, 51, 139, 199, 200

  \indexspace

  \item variability
    \subitem heterogeneity, \see {model, homogeneity of variance}{}
  \item vector
    \subitem atomic, 62, 72, 84, 100
    \subitem character, 17, 20, 23, 62, 64, 66--68, 72, 77, 78, 83, 208, 
		210, 242
      \subsubitem number of characters, 77
      \subsubitem splitting, 77
    \subitem complex, 62, 66, 83
    \subitem concatenation, 65
    \subitem logical, 23, 62, 63, 66, 67, 72, 78, 83
    \subitem numeric, 17, 21, 23, 25, 62, 64, 66--68, 72, 73, 78, 83, 
		85, 86, 100, 101, 104, 210, 242
    \subitem recursive (list), 20, 23, 30, 62, 66--68, 70, 72, 76, 80, 
		83, 84, 94, 100, 104, 210
    \subitem subset, 62, 63, 67, 68, 85

  \indexspace

  \item working directory, \see {R session}{}
  \item workspace, \see {R session}{}

\end{theindex}