s(x)

generalized additive models

nonparametric smoothers in gam

sample

for shuffling and randomization

prob=p

rows from a dataframe

runs test

sample size

shuffling rows of a matrix

the game of craps

unequal probabilities

sample(c(1,0,-1),1)

random walk

sample(replace=T)

bootstrap

bootstrap with glm

sample cases

bootstrap

samples

plots for single samples

sample size

and standard error of mean

by matrix multiplication

difference to be detected

for count data

in sample

introduction

power analysis

power calculations

problems with notches

sample size = 30

rule of thumb

sample variance

calculating variance

confidence interval

scaled chi squared distribution

sampling with replacement

bootstrap

replace=T

sampling without replacement

hypergeometric distribution

sans

font families for text

sapply

%in%

is.factor

is.numeric

anonymous functions

in a for loop for simulating dynamics

introduction

lags for partial correlation plots

na.omit

paste

with sample

with seq

sapply with mean

yields

saturated model, 3-dimensional contingency table

admissions data

definition

for contingency tables

residual deviance = 0

Schoener's lizards

save

default graphic parameters

introduction

savehistory

saving the history file

saving a list

to file

saving data from R

write.table

saving graphics to file

pdf or ps

saving the history file

savehistory

scale

different models on comparable scales

introduction

scale-dependent correlations

scale dependence

quadrat counts

scale of measurement

model choice

scale on the y axis

ylim

scale parameter

overdispersion

standardized residuals

scale the axes for multiple variables

type="n"

scale the y axis

ylim

scan

"\n"

as.data.frame

compared with read.table

creating a header row

data entry from keyboard

input a data file

keyboard data entry

multi.line=T

na.omit

nlines

paste data from the keyboard

removing NA

sep

skip

scatter

measure using r²

scatterplot

and causation

introduction

legend with multiple colours

linear regression

logarithmic axes

xyplot

scatterplot matrix

splom

Schoener's lizards

a complex contingency table

conversion to proportion data

scientific importance

vs. statistical significance

scientific notation

exponents e

scoping rules

introduction

scree plot

principal components analysis

screen

changing default settings

screen prompt

>

sd

standard deviation

se

function to compute standard error of a mean

search

lists attached packages and dataframes

seasonal component of a time series

stl

seasonal data

cycle length

sin and cos

time series analysis

seasonal decomposition of time series by loess

illustration

stl

seBars

function

sec

seconds

second(s)

%S second as decimal number (00–61, allowing for two ‘leap seconds’)

units of slopes of regressions with dates and times

second subscript

column

seed

for random number generator

SELECT

a list of the variables required (or ∗ for all variables) in SQL

selecting columns in a dataframe

grep

selecting only certain rows from the dataframe

subset or subscripts

selecting rows of a dataframe

logical subscripts

which

selection

using logical subscripts

self-starting functions

nonlinear regression

sem

path analysis

semicolon

delimited files

SemiPar

package

semivariogram

introduction

sep

separator in paste

using scan

sep="\n"

new line separators with scan

sep="\t"

tab separation

separators

in data files

separators with scan

sep="\n"

sep="\t"

seq

as subscripts

dates and times

drawing a smooth curve

sequence generation

smoothing

with sapply

x values for a smooth plot

sequence

successive sequences of differing lengths

sequence creation

:

sequence generation

seq

sequences of dates and times

sequential palettes

RColorBrewer package

serial correlation

assumptions

serial correlation in the residuals

dealing with pseudoreplication

Durbin Watson

serial dependence

residuals

time series analysis

serif

font families for text

set the working directory

setwd

set theory

%in%

intersect

setdiff

setequal

union

set.seed

for random number generator

setdiff

order matters

set theory

setequal

logical function

sets

TEX-like rules

settlement of propagules

metapopulation dynamics

setwd

file paths

set the working directory

sex discrimination

prop.test

sex ratio

binom.test

sex ratio of twins

probabilities

shading

density and angle

shading under a curve

polygon

shape

gamma distribution

of plotting region

shape file

creating polygon lists

shape of the plotting region

plt

shapes

adding shapes to a graph

shapes of graphs on the same page

layout

shapes of the beta distribution

illustration

shapiro.test

normality tests compared

test of normality

shingles

with coplot

shrinkage

Bayesian statistics

in mixed effects models

in nonlinear mixed models

in regression parameters

random effects meta-analysis

shuffle residuals

bootstrap

shuffling

randomization

shuffling rows of a matrix

sample

side

with jitter

sigma

TEX-like rules

sigmoid curves

sign.test

exact binomial test

sign test

introduction

signif

specify number of significant digits

significance

data dredging (at α = 0.05)

main effects in ANOVA

significance in graphics

notches

significance level

power of the test (β = 0.8)

significant digits

signif

signrank

Wilcoxon signed rank

sill

variogram

simple is best

Occam's razor

simplification

model simplification

step-wise deletion

simulated time series

simulation in two dimensions

random walk

simulation models

introduction

recall same random numbers

sin

drawing bubble plots

introduction

polynomial approximation

sine in radians

sin and cos

seasonal data

sine in radians

sin

single samples

introduction

plots

size distribution

non-normal

size of axis numbers

cex.axis

size of plotting symbol

cex

size of text

size of text labels

cex.lab

skew

box-and-whisker plot

comparing two distributions

confidence interval by bootstrap

empirical cumulative distribution function

graphical test of normality

in histograms

introduction

light data

lognormal distribution

negative binomial distribution

normality plot

t-test of significance

Weibull distribution

skip

using scan

slope

extracting from summary(model)

linear regression

model specification

plots of se of slope

significant differences

summary.lm

units with dates and times

small samples

Fisher's exact test

smallest plotting symbol

pch="."

smoking and weight

interaction

smooth curves

generating x values

smooth density function overlay

hist

smoothers

non-parametric curves

smoothing

panel.smooth

smooth line from a logistic model

binary response variable

smooth line from a log-linear model

predict with exp

smooth lines

draw using curve

smooth lines for drawing curves

deviance

generating x values

snd

standard normal distribution

socketConnection

connections

solid line (the default)

lty = 1

solve

solving linear equations

solving linear equations

matrix notation

sort

a dataframe by rows

function to sort a vector into ascending order

sort a vector into ascending order

sort(x) a sorted version of x

with unique

sort

on multiple variables

sorting

introduction

sorting by date

sources of variation

ANOVA table for regression

spaced-out

regular patterns

spaces

∼∼ for extra spaces in graph titles

in variable names

spatial correlation

anisotropy

Geary's C

generalized least squares

Moran's I

multiple regression

paired t test

spatial correlation structures

introduction

spatial covariates

in linear models

spatial dynamics

simulation models

spatial dynamics of host-parasite interaction

coupled map lattice

pattern generation

spatial dynamics of the random walk

spatial errors

form=∼latitude+longitude

spatial functions for kriging and point pattern analysis

library

spatial model that is not spatially explicit

metapopulation dynamics

spatial point processes

aggregated

random

regular

spatial pseudoreplication

mixed effects models

spatial statistics

introduction

spatially explicit density dependence

coexistence of species

spatially explicit processes

spatstat

installed package

packages for spatial statistics

spdep

installed package

packages for spatial statistics

spdep package

introduction

Spearman

rank correlation

species

counting species names

species area relationship SAR

piecewise regression

species coexistence

spatially explicit density dependence

spectral analysis

periodogram

spectrum

time series analysis

spectrum

spectral analysis

spherical spatial correlation

corSpher

spine plots and spinograms

split

for coloured ANCOVA plots

for plotting in different colours

split a character string

strplit

split plot experiment

example

introduction

mixed effects models

model formulae

split the plotting region

fig

split.screen

multiple screens on a single device

splom

panel plots

scatterplot matrix

spread of x values

efficient regression designs

spreadsheet

for data entry

SQL

problems involved with quotation marks

Structured Query Language

sqlQuery

examples from Northwind

introduction

writing a query in R

sqrt

square root

square

joints of lines

square plotting region

pty="s"

square root

sqrt

transformations

square root of the response

constancy of variance

square root symbol

TEX-like rules

srt

character string rotation

srt=45

rotating long bar labels to eliminate overlap

SSA

calculations

treatment sum of squares

SSasymp

asymptotic regression model

SSasympOff

asymptotic regression model with an offset

SSasympOrig

asymptotic regression model through the origin

SSbiexp

biexponential model

SSC

contrast sum of squares

SSE

error sum of squares

in one-way ANOVA

matrix notation

unexplained variation

SSfol

first-order compartment model

SSfpl

four-parameter logistic model

SSgompertz

Gompertz growth model

S-shaped curve

binary response variable

S-shaped functions

non-linear models

SSlogis

logistic model

SSmicmen

Michaelis–Menten model

SSR

explained variation in regression

in ANCOVA

matrix notation

SST

calculations

total sum of squares

SST=SSE

means identical

SST>SSE

means different

SSweibull

Weibull growth curve model

SSX

in ANCOVA

introduction

standard errors in regression

SSXY

corrected sum of products

in ANCOVA

SSY

matrix notation

total sum of squares (also as SST)

y∼1 residual deviance

stable point equilibrium

population dynamics

stack

create a dataframe from columns of vectors

standard deviation

maximum likelihood

sd

standard error

of skew

predicted values in linear regression

standard error of a mean

anonymous function in tapply

effect of sample size

for error bars

introduction

with tapply

standard error of a slope

regression

standard error of an intercept

regression

standard error of mean

as error bars

standard error of the difference between two means

calculations

Helmert contrasts

summary.lm

with contrasts

standard error of the intercept

in ANCOVA

standard error of the summary effect

fixed-effect meta-analysis of scaled differences

standard errors

model.tables

standard errors in ANOVA

understanding summary.lm

standard errors in regression

optimal designs

standard normal distribution

mean = 0 sd = 1

z plus and minus three quantiles

standardized residuals

background

staple (end of the whisker)

staplecol

staplelty

staplelwd

staplewex

staplecol

colour

staplelty

line type

staplelwd

line width

staplewex

width expansion

start

initial parameter estimates

stationarity

time series analysis

statistic function for boot

introduction

non-linear regression

Statistical Genetics

task views

statistical models

background

matrix notation

summary of steps taken

statistical significance

vs. scientific importance

statistics

choosing the right test

Statistics for the Social Sciences

task views

status, 1∗(death>0)

dead or last seen alive

stderr

connections

stdin

connections

stdout

connections

step for model simplification

binary response variable

binomial glm

contingency table analysis

factorial ANCOVA

model simplification in ANCOVA

Schoener's lizards as proportion data

simplification in coxph models

simplification in survivorship models

step function

compared with a smoother

illustration

stepAIC

negative binomial errors

stepped lines

on plots

stepped survivorship curve

Kaplan–Meier object

step-wise deletion

example from competition experiment

model simplification

stl

data series

residuals

seasonal component

seasonal decomposition of time series by loess

trend

stop

message when a function would fail

str

mixed effects model

of a linear model

structure of an R object

table of UCBA admissions

time series object

with lists

straight lines

linear models

linear regression assumptions

string rotation

srt

strings

%in%

charmatch

grep

gsub

length

nchar

regexpr

sub

which

stripchart

introduction

stripplot

one-dimensional scatterplot

panel plots

strplit

split a character string

using words

strptime

%a abbreviated weekday name

%A full weekday name

%b abbreviated month name

%B full month name

%c date and time, locale-specific

%d day of the month as decimal number (01–31)

%H hours as decimal number (00–23) on the 24-hour clock

%I hours as decimal number (01–12) on the 12-hour clock

%j day of year as decimal number (0–366)

%M minute as decimal number (00–59)

%m month as decimal number (0–11)

%p AM/PM indicator in the locale

%S second as decimal number (00–61, allowing for two ‘leap seconds’)

%U week of the year (00–53) using the first Sunday as day 1 of week 1

%W week of the year (00–53) using the first Monday as day 1 of week 1

%w weekday as decimal number (0–6, Sunday is 0)

%x date, locale-specific

%X time, locale-specific

%Y year with century

%y year without century

%Z time zone as a character string (output only)

examples

extract dates and times from a character string

in dataframes

non-standard examples

strsplit

with readLines

structural equation modelling

introduction

structural non-linearity

mis-specification of the model

structure in the data

multivariate statistics

structure of an R object

str

Structured Query Language

SQL

Student's t

critical value qt

introduction

t

Student's t compared with normal

fat tails

Student's t test

background

null hypothesis

t.test

test statistic

sub

text substitution

subjectivity

narrative reviews

subscript 1

row

subscript 2

column

subscripts (aka indices)

!duplicated

%in%

complicated formatting of axis labels

duplicated

extract a minimum value

for defining neighbours

for ordering points on a graph

grep

in plotting for ANCOVA

introduction

jackknife

match

on dataframes

on lists

produced by match

repeating rows in a dataframe

shortening dataframes

TEX-like rules

understanding the order function

using logical subscripts

using sequences

using which

subscripts from a list

[[1]]

subset

graphics for mixed effects models

in plots

model options

model-checking plot

omit certain values from a model

removing pseudoreplication

subset or subscripts

selecting only certain rows from the dataframe

substitute

deparsing variable names

drawing bubble plots

mathematical and other symbols on plots

substr

extract part of a character string

substring

subtitle colour

col.sub

subtraction

-

success

Bernoulli distribution

success or failure

binary response variable

proportion data

sum

add the values within a vector

logical arithmetic

sum(x) total of all the values in x

sum contrasts

in ANCOVA

worked example

sum of products

%∗%

sum of squares

calculating variance

function to calculate

sum of two variances

summarizing dataframes

aggregate

by

summary

dataframe

dataframe summary

for model objects

light data

single samples

statistical models

with lists

summary.aov

ANOVA table for regression

effect of dropping one point

extracting information using list subscripts [[]]

model summaries compared

vs. summary.lm

with lm

summary.lm

differences between intercepts

differences between means

differences between slopes

extracting information using list subscripts [[]]

factorial ANCOVA

in factorial experiments

in one-way ANOVA

intercept

linear predictor

model summaries compared

orthogonal polynomial contrasts

standard error of a slope

standard error of an intercept

standard error of the difference between two means

vs. summary.aov

summary statistics

aggregate

by

tapply

summary statistics by groups

summary(model)

attributes

sums of ranks

tapply

sums of square

or absolute values

sums of squares

ANOVA table for regression

famous five

in hierarchical designs

sums of squares in ANCOVA

order matters

sunflowerplot

plots with multiple copies of data points

sunspots

time series plot

superscripts

complicated formatting of axis labels

TEX-like rules

suppressing correlations in lmer output

print(cor=F)

surf.ls

trend surface

Surv(death,status)

Kaplan–Meier survivorship object

survfit

plot a Kaplan–Meier survivorship object

survival

logical arithmetic

survival analysis

Cox proportional hazards model

introduction

task views

survival analysis, including penalised likelihood

survival library

survival times

ranks of survival time

survivor function

Weibull distribution

survivorship curves

for grouped data

Kaplan-Meier object

Types I, II and III

survreg

with exponential errors

survreg and coxph

comparison on same data

model choice

sweep

apply a function to a specified margin of a matrix

with dataframes

switch

execute different parts of a function

symbol size for outliers

outcex

symbols

add a legend to a plot

choice

colour schemes

complicated formatting of axis labels

for plotting

multiple time series

plots with many variables

Sys.time

introduction

system.time

timing operations

systematic review

meta-analysis

t

hypothesis testing

Student's t

transpose a matrix or a dataframe

t = 2

rule of thumb

t.test

paired samples

Student's t test

tab

multiple tabs

tab character

"\t"

tab delimited files

using scan

table

binary response variable

compared with tabulate

count characters

count the occurrences of each value

counting species names

from a dataframe

in a relational database

introduction

in Northwind

murders by region

random numbers from a Poisson distribution

random numbers from the geometric distribution

re-order a multidimensional table with aperm

str

testing the random number generator

two-dimensional

with write.table

table objects

chisq.test

table to dataframe

as.data.frame

introduction

tables from a relational database

joining tables in queries

tabulate

compared with table

tags

exact matching on tags

tail

dataframe operations

producing a shorter summary dataframe

tails

two-tailed test

tails of a distribution

colour using polygon

introduction

polygon

tan

introduction

tangent in radians

tangent in radians

tan

tapered or cylindrical timber

offsets

tapply

anonymous function for standard error

calculating variances

create table of means

for sums of ranks

introduction

list of classifying variables

mean temperatures

na.rm=T

producing a shorter summary dataframe

to barplot

trim option

variance in temperatures

with dates and times

tapply for factorial experiments

target

using all.equal

target cell

first-order neighbours

task views

Analysis of Ecological and Environmental Data

Analysis of Pharmacokinetic Data

Analysis of Spatial Data

Bayesian Inference

Chemometrics and Computational Physics

Clinical Trial Design, Monitoring, and Analysis

Cluster Analysis & Finite Mixture Models

Computational Econometrics

Design of Experiments (DoE) & Analysis of Experimental Data

Differential Equations

Empirical Finance

Graphic Displays & Dynamic Graphics & Graphic Devices & Visualization

Graphical Models in R

High-Performance and Parallel Computing with R

Machine Learning & Statistical Learning

Medical Image Analysis

Multivariate Statistics

Natural Language Processing

Official Statistics & Survey Methodology

on CRAN

Optimization and Mathematical Programming

packages

Phylogenetics, Especially Comparative Methods

Probability Distributions

Psychometric Models and Methods

Reproducible Research

Robust Statistical Methods

Statistical Genetics

Statistics for the Social Sciences

Survival Analysis

Time Series Analysis

tau

Kendall's tau

tau squared

between-study variance in random effects meta-analysis

taxonomic keys

tree models

Taylor's power law

quasi-likelihood

variance mean relationships

t compared with normal

fat tails

te(x)

tensor product smooths

temporal correlation

model criticism

multiple regression

temporal dynamics

simulation models

temporal pseudoreplication

binary response variable

introduction

longitudinal data

mixed effects models

non-linear time series models

tensor product smooths

te(x)

terms

str of linear model

terrain.colors

illustration

tessellation

introduction

testing for a trend in a time series

testing for equality

real numbers

testing for missing values

is.na

testing the random number generator

runif

test of normality

qqnorm

tests for non-linearity

efficient regression designs

tests of linear models

lmtest

test statistic

contingency tables

fixed-effect meta-analysis of scaled differences

standard error of the difference between two means

Student's t test

TEX-like rules

complex mathematical expressions

text

centering

complex mathematical expressions

font families

for factor levels

graphics parameters explained

identifying individual points on graphs

in plots

names on maps

on plots

overlaying labels on partition.tree

substitution

vertical offset

with locator

text editor

text in the outer margin

mtext

text justification

adj

text outside the plottting region

xpd = TRUE

text size

cex

The R Book

URL

The R Journal

thicker lines for axes

lwd

thin plate regression spline

generalized additive models

three-dimensional array

aperm

three-dimensional plots

contour

filled.contour

image

introduction

wireframe

three-dimensional scatterplots

cloud

three-dimensional summary tables

with tapply

three parameter

logistic

threshold

binary response variable

defining the threshold for step function using tree models

generalized additive models

illustration

in regression

migration rate in metapopulation models

recursive partitioning

threshold detection

efficient regression designs

tic mark labels

axis

tick marks on the axes

background

illustration

tilde ∼

statistical models

tilde dot minus

update

time(s)

%X Time, locale-specific

differences between two times

option for rep

reading from file

time differences

rounding

times and dates

introduction

reading data from file

time series

autocorrelation

first-order autoregressive process

groupedData

Nicholson's blowflies

non-linear regression

output of a plant-herbivore model

partial autocorrelation

simulations

Yule–Walker equation

time series analysis

correlation structure

introduction

mixed effects models

moving average

panel plots

seasonal data

serial dependence

spectral analysis

stationarity

task views

trend

time series models

arima

autoregressive (AR) models

autoregressive moving average (ARMA) models

loops

moving average (MA) models

population dynamics

time series object

ts

time series plot

plot

plot.ts

ts.plot

time series seasonal decomposition by loess

stl

time-to-failure data

introduction

time zone

%Z time zone as a character string (output only)

timing operations

proc.time

system.time

Tinn-R

text editor

tips

good programming

title

graphics parameters explained

in a legend

in legends

titles for graphs

main

tmd

panel plots

Tukey mean–difference plot

to

sequence generation

tolower

lower case

top

axis = 3

margin = 3

topo.colors palette

illustration

T or TRUE

problems

total sum of squares

SSY or SST

toupper

upper case

trade-off

Type I and Type II error rates

transformation

changes curvature

log for decay function

reciprocals

transformation of the explanatory variables

binary response variable

transformations

antilog

arcsine

cube root

introduction

linear models

linear regression

log

logit

log-log

model choice

objectives

reciprocal

square root

standard normal distribution

transform both axes

log="xy"

transform x axis

log="x"

transform y axis

log="y"

transient dynamics

simulation models

transients

population dynamics

transpose a dataframe

t

transpose an array

aperm

treatment contrasts

in ANCOVA

in one-way ANOVA

minimal adequate model

summary.lm

worked example

treatment sum of squares

ANOVA

SSA=SST-SSE

treatment totals

in one-way ANOVA

tree

classification trees

installed package

models

tree models

defining the threshold for step function

humped curves

introduction

print

to produce taxonomic keys

tree models to check for interaction

multiple regression

ozone.data

trellis graphics

introduction

trend

Nicholson's blowflies

stl

time series analysis

trend in a time series

statistical tests

trend surface

surf.ls

trigonometric functions

introduction

trim

function to drop high and low values

with mean in tapply

with tapply

trimming data

pmin and pmax

tripack package

triple dot

variable numbers of arguments

TRUE and FALSE

combinations of values

truehist

Old Faithful data

trunc

truncate towards zero

try

function allows failure

ts

class of time series objects

create a time series object

ts.plot

time series plot

t test

power.t.test

Tukey mean–difference plot

tmd

Tukey's honest significant differences

multiple comparisons using TukeyHSD

TukeyHSD

multiple comparisons

Tukey's five number summary

fivenum

t value

summary.lm

two-by-two contingency tables

log-linear model of count data

Mendel's peas

two-category table

binom.test

two-dash line

lty = 6

two graphs with different y axes on the same x axis

two-sample tests

introduction

two tailed test

in one-way ANOVA

two-tailed test

Fisher's exact test

Type I error

contingency tables

hypothesis testing

power analysis with (α = 0.05)

Student's t test

Type I error rate

(α = 0.05)

Type II error

contingency tables

power analysis (with β = 0.8)

Type II error rate (1-β = 0.2)

Type II survivorship

constant risk of death

type="b"

both points and lines

joining the dots

type="l"

line (lower case L not number 1)

smoothing

type="n"

multi-coloured scatterplot

names on maps

scale the axes for multiple variables

type="response"

back-transform the logistic

type="s"

negative binomial distribution

plot of binomial coefficients

plot of x factorial

plotting stepped lines across first

type="S"

plotting stepped lines up first

unbiased risk estimator

gam

unbiased variance-minimizing estimators

maximum likelihood

unbound symbols

introduction

uncertainty

in prediction

plots of standard error of slope

predicted values in linear regression

unclass

convert factor levels to numbers

with write.table

unequal probabilities

chisq.test

sample

unexplained variation

deviance

SSE

unif

uniform distribution

uniform distribution

introduction

unif

uniform errors

illustration

uninformative factor levels

random effects

uninstall

R

union

set theory

unique

removing duplicate rows from a dataframe

select the unique values from an object

with sort

unlist

extract values from summary.aov

readLines

with AIC

with as.numeric

with dataframes

with gregexpr

unplanned comparisons

contrasts

unreliability estimates for the parameters

analysis of variance

regression

unreliability measures

introduction

meta-analysis

slope and intercept by MCMC

standard error of a mean

unstable parameter estimates

multiple regression

update

binary response variable

contingency table analysis, 605

for model objects

introduction

log-linear model of count data

model simplification

model simplification in ANCOVA

upper case

of initial letters

toupper

upper limit on the summary effect

fixed-effect meta-analysis of scaled differences

url

connections

data input from the web

The R Book

urns with balls

hypergeometric distribution

U-shaped curves

beta distribution

biexponential model

quadratic terms

usr

current x and y maxima and minima of the plotting region

var

comparing two variances

covariance

function for variance

na.rm=T

var(x) sample variance of x

var(x,y)

covariance of x and y

var.test

comparing two variances

variance ratio test

variable names

case sensitive

choice

no spaces in

variable selection

model choice

multiple regression

variability

advantages of logarithms

variance

age at death

Bernoulli distribution

binomial distribution

calculated with tapply

comparing two distributions

comparing two variances

function

in comparing means

inverse variances as weights

power analysis

uses of

with frequency data

variance components analysis

dealing with pseudoreplication

introduction

rats example

variance covariance matrix for model parameters

vcov

variance function

standardized residuals

variance mean ratio

comparing data with a Poisson distribution

count data from quadrats

negative binomial distribution

Poisson distribution

variance mean relationship

binomial

illustration

model-checking plot

overdispersion

proportion data

quasi-likelihood

Taylor's power law

variance of a difference

correlation

correlation coefficient

paired samples

sum of the component variances

variance of a sum

sum of the component variances

variance of the summary effect

fixed-effect meta-analysis of scaled differences

variance ratio test

var.test

variance-minimizing estimators

maximum likelihood

variances

correlation coefficient

variances unequal

gls

Variogram

form=∼latitude+longitude

gls

illustration

introduction

nugget

range

sill

vcov

variance covariance matrix for model parameters

vector

in paste function

into matrix using dim

length

vector functions

colMeans(x) column means of dataframe or matrix x

colSums(x) column totals of dataframe or matrix x

cor(x,y) correlation between vectors x and y

cummax(x) vector of non-decreasing numbers which are the cumulative maxima of the values in x up to this point

cummin(x) vector of non-increasing numbers which are the cumulative minima of the values in x up to this point

cumprod(x) vector containing the product of all of the elements up to that point

cumsum(x) vector containing the sum of all of the elements up to that point

ifelse

introduction

length

max(x) maximum value in x

mean(x) arithmetic average of the values in x

median(x) median value in x

min(x) minimum value in x

order(x) an integer vector containing the permutation to sort x into ascending order

pmax(x,y,z) vector, of length equal to the longest of x, y or z, containing the maximum of x, y or z for the

pmin(x,y,z) vector, of length equal to the longest of x, y or z, containing the minimum of x, y or z for the

quantile(x) vector containing the minimum, lower quartile, median, upper quartile, and maximum of x

range(x) vector of min(x) and max(x)

rank(x) vector of the ranks of the values in x

rowMeans(x) row means of dataframe or matrix x

rowSums(x) row totals of dataframe or matrix x

sort(x) a sorted version of x

sum(x) total of all the values in x

var(x) sample variance of x

vector operations

c(x,y,z) concatenation of objects x, y, z

shorter vector is recycled

version

updating R

vertical line

abline(v=x)

vertical tab

"\v"

view file names

dir

vis.gam, 3-D graphics

volcano

wireframe

Voronoi object

voronoi.mosaic

vote-counting

meta-analysis

waiting time

negative binomial distribution

wallpaper

background colours

wday

day of the week

weakest link analysis

Weibull distribution

weekday abbreviated name

%a abbreviated weekday name

weekday full name

%A full weekday name

weekday number

%w weekday as decimal number (0–6, Sunday is 0)

weekdays

date to name

from sequences of dates

week number

%W week of the year (00–53) using the first Monday as day 1 of week 1

week of the year

%U week of the year (00–53) using the first Sunday as day 1 of week 1

weibull

Weibull distribution

Weibull distribution

death risk with age

introduction

non-linear models

survreg

weibull

Weibull growth curve model

SSweibull

weight

fixed-effect meta-analysis of scaled differences

weighted by sample size

proportion data

weighted mean summary effect

fixed-effect meta-analysis of scaled differences

weights

inverse variances

meta-analysis

model options

weights list object

class lw

what with scan

character

complex

integer

list

logical

WHERE

specification of which rows of the table(s) are required in SQL

which

address within vectors

character strings

closest values

error checks

finding maxima and minima

is.na

names on maps

piecewise regression

produces a vector of subscripts

to find nearest neighbours

to select rows from a dataframe

with lists

which.max

finding maxima

which.min

finding minima

while

binary representation of a number

creating a loop

Fibonacci series

whisker(s)

box-and-whisker plot

whiskcol

whisklty

whisklwd

whiskcol

colour

whisklty

line type

whisklwd

line width

white is rgb(1, 1, 1)

rgb

white noise

simulated time series

width

of bins for histograms

postscript or pdf window

width expansion

outwex

staplewex

widths of lines

lwd

wiggliness

penalty in gam

wilcox

Wilcoxon rank

wilcox.test

light data

Wilcoxon rank sum test

Wilcoxon

distribution of ranks

Wilcoxon rank

wilcox

Wilcoxon rank sum test

background

Wilcoxon signed rank

signrank

wildcards in SQL queries

LIKE

Wilde, Oscar

quote

WinBUGS

Bayesian inference Using Gibbs Sampling

Windows Version 7

creating a DSN channel

frequently asked questions

installation

windows(7,4) for par(mfrow = c(1,2))

chi squared distribution

exponential function

function for model-checking

logistic distribution

predict(type="response")

principal components analysis

sexratio

two graphs side by side

with histograms

windows(7,7)

default frame

windows(9,7)

for a rectangular map

wireframe, 3D surfaces (similar to persp plots)

illustration

panel plots

three-dimensional plots

with

instead of attach

with or attach

without replacement

sampling

word count

table

worked examples of function

example

working directory

setwd

worms

introduction

sorted using order

wrap-around margins

edge effects in spatial simulations

write

data to file

write.table

introduction

for components of lists

saving a dataframe to file

writeClipboard

clipboard

writing a function

factorial

writing data from R to file

introduction

Writing R Extensions

manual

writing R function

introduction

wrong model

misspecification

x! = x × (x - 1) × (x - 2)×· · ·×3 × 2

factorial

x axis

axis = 1

error bars in x and y directions

explanatory variable

x axis log scale

log="x"

xaxt="n"

for maps

names on maps

no tick marks

phase planes

xlab

deparsing variable names

introduction

xlab=""

blank axes labels

xlevels

str of linear model

xlim

scale the x axis

x measured without error

linear regression assumptions

xor(x,y)

exclusive OR

xpd = TRUE

text outside the plotting region

xtabs

cross tabulations

x values

efficient regression designs

xy.error.bars

function

xyplot

panel plots

scatterplot

xzfile

connections

y

response variable

y axis

axis = 2

two graphs with different y axes on the same x axis

y axis log scale

log="y"

y∼1

estimate the intercept

fitting the null model

yaxt="n"

for maps

names on maps

no tick marks

phase planes

yday

day of the year

year

year number

year with century

%Y year with century

year without century

%y year without century

years and months

tapply

yes or no (binary response)

introduction

proportion data

ylab

deparsing variable names

introduction

ylab=""

blank axes labels

ylim

scale on the y axis

Yule–Walker equation

time series

z

quantile of the normal distribution

standard normal distribution

zero

count data

testing for zeros

zero term

negative binomial distribution

Poisson distribution

zeros in tables

tabulate rather than table

α

Type I error rate (0.05)

β

power of the test (0.8)

λ

per-capita multiplication rate

π

built-in constant (pi = 3.14159)

ρ

Pearson's rho

τ

Kendall's tau

τ²

between-study variance in random effects meta-analysis