Appendix D 函数和变量索引

• !: 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
• ^: Vector arithmetic
• 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
• 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: Character vectors
• C: Contrasts
• c: Concatenating lists
• c: Vectors and assignment
• c: The concatenation function c() with arrays
• 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: Multiplication
• crossprod: Index arrays
• cut: 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
• diag: Multiplication
• dim: Arrays
• dotchart: Display graphics
• drop1: 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
• example: Getting help
• exp: Vector arithmetic
• 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
• glm: The glm() function
• help: Getting help
• help.search: Getting help
• help.start: Getting help
• hist: Examining the distribution of a set of data
• hist: Display graphics
• identify: Interacting with graphics
• if: Conditional execution
• ifelse: Conditional execution
• image: Display graphics
• is.na: Missing values
• is.nan: Missing values
• jpeg: Device drivers
• ks.test: Examining the distribution of a set of data
• legend: Low-level plotting commands
• length: The intrinsic attributes mode and length
• length: Vector arithmetic
• 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
• log: Vector arithmetic
• lqs: Some non-standard models
• lsfit: Least squares fitting and the QR decomposition
• mars: Some non-standard models
• max: Vector arithmetic
• mean: Vector arithmetic
• min: Vector arithmetic
• mode: The intrinsic attributes mode and length
• NA: Missing values
• NaN: Missing values
• ncol: Matrix facilities
• next: Repetitive execution
• nlm: Maximum likelihood
• nlm: Nonlinear least squares and maximum likelihood models
• nlm: Least squares
• nlme: Some non-standard models
• nrow: Matrix facilities
• optim: Nonlinear least squares and maximum likelihood models
• order: Vector arithmetic
• ordered: Ordered factors
• outer: The outer product of two arrays
• 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
• qqline: Examining the distribution of a set of data
• qqline: Display graphics
• qqnorm: Display graphics
• qqnorm: Examining the distribution of a set of data
• qqplot: Display graphics
• qr: Least squares fitting and the QR decomposition
• quartz: Device drivers
• 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
• 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: Updating fitted models
• step: Generic functions for extracting model information
• sum: Vector arithmetic
• summary: Generic functions for extracting model information
• summary: Examining the distribution of a set of data
• svd: Singular value decomposition and determinants
• T: Logical vectors
• t: Generalized transpose of an array
• t.test: One- and two-sample tests
• table: Frequency tables from factors
• table: Index arrays
• 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: The function tapply() and ragged arrays
• var: Vector arithmetic
• var.test: One- and two-sample tests
• vector: Vectors and assignment
• while: Repetitive execution
• wilcox.test: One- and two-sample tests
• windows: Device drivers
• X11: Device drivers
• |: Logical vectors
• ||: Conditional execution
• ~: Formulae for statistical models