# The R Stats Package

## Documentation for package ‘stats’ version 4.1.0

- DESCRIPTION file.
- Code demos. Use demo() to run them.

## Help Pages

A B C D E F G H I K L M N O P Q R S T U V W X misc

stats-package | The R Stats Package

## -- A --

acf | Auto- and Cross- Covariance and -Correlation Function Estimation
acf2AR | Compute an AR Process Exactly Fitting an ACF
add.scope | Compute Allowed Changes in Adding to or Dropping from a Formula
add1 | Add or Drop All Possible Single Terms to a Model
addmargins | Puts Arbitrary Margins on Multidimensional Tables or Arrays
aggregate | Compute Summary Statistics of Data Subsets
AIC | Akaike's An Information Criterion
alias | Find Aliases (Dependencies) in a Model
anova | Anova Tables
anova.glm | Analysis of Deviance for Generalized Linear Model Fits
anova.lm | ANOVA for Linear Model Fits
anova.mlm | Comparisons between Multivariate Linear Models
ansari.test | Ansari-Bradley Test
aov | Fit an Analysis of Variance Model
approx | Interpolation Functions
approxfun | Interpolation Functions
ar | Fit Autoregressive Models to Time Series
ar.burg | Fit Autoregressive Models to Time Series
ar.burg.default | Fit Autoregressive Models to Time Series
ar.mle | Fit Autoregressive Models to Time Series
ar.ols | Fit Autoregressive Models to Time Series by OLS
ar.yw | Fit Autoregressive Models to Time Series
ar.yw.default | Fit Autoregressive Models to Time Series
arima | ARIMA Modelling of Time Series
arima.sim | Simulate from an ARIMA Model
arima0 | ARIMA Modelling of Time Series - Preliminary Version
ARMAacf | Compute Theoretical ACF for an ARMA Process
ARMAtoMA | Convert ARMA Process to Infinite MA Process
as.dendrogram | General Tree Structures
as.dist | Distance Matrix Computation
as.formula | Model Formulae
as.hclust | Convert Objects to Class hclust
as.hclust.dendrogram | General Tree Structures
as.matrix.dist | Distance Matrix Computation
as.stepfun | Step Functions - Creation and Class
as.ts | Time-Series Objects
asOneSidedFormula | Convert to One-Sided Formula
ave | Group Averages Over Level Combinations of Factors

## -- B --

bandwidth.kernel | Smoothing Kernel Objects
bartlett.test | Bartlett Test of Homogeneity of Variances
Beta | The Beta Distribution
BIC | Akaike's An Information Criterion
binom.test | Exact Binomial Test
Binomial | The Binomial Distribution
binomial | Family Objects for Models
biplot | Biplot of Multivariate Data
biplot.princomp | Biplot for Principal Components
Box.test | Box-Pierce and Ljung-Box Tests
bw.bcv | Bandwidth Selectors for Kernel Density Estimation
bw.nrd | Bandwidth Selectors for Kernel Density Estimation
bw.nrd0 | Bandwidth Selectors for Kernel Density Estimation
bw.SJ | Bandwidth Selectors for Kernel Density Estimation
bw.ucv | Bandwidth Selectors for Kernel Density Estimation

## -- C --

C | Sets Contrasts for a Factor
cancor | Canonical Correlations
case.names | Case and Variable Names of Fitted Models
case.names.lm | Case and Variable Names of Fitted Models
Cauchy | The Cauchy Distribution
cbind.ts | Time-Series Objects
ccf | Auto- and Cross- Covariance and -Correlation Function Estimation
chisq.test | Pearson's Chi-squared Test for Count Data
Chisquare | The (non-central) Chi-Squared Distribution
cmdscale | Classical (Metric) Multidimensional Scaling
coef | Extract Model Coefficients
coef.default | Extract Model Coefficients
coefficients | Extract Model Coefficients
complete.cases | Find Complete Cases
confint | Confidence Intervals for Model Parameters
constrOptim | Linearly Constrained Optimization
contr.helmert | (Possibly Sparse) Contrast Matrices
contr.poly | (Possibly Sparse) Contrast Matrices
contr.SAS | (Possibly Sparse) Contrast Matrices
contr.sum | (Possibly Sparse) Contrast Matrices
contr.treatment | (Possibly Sparse) Contrast Matrices
contrasts | Get and Set Contrast Matrices
convolve | Convolution of Sequences via FFT
cooks.distance | Regression Deletion Diagnostics
cooks.distance.lm | Regression Deletion Diagnostics
cophenetic | Cophenetic Distances for a Hierarchical Clustering
cor | Correlation, Variance and Covariance (Matrices)
cor.test | Test for Association/Correlation Between Paired Samples
cov | Correlation, Variance and Covariance (Matrices)
cov.wt | Weighted Covariance Matrices
cov2cor | Correlation, Variance and Covariance (Matrices)
covratio | Regression Deletion Diagnostics
cpgram | Plot Cumulative Periodogram
cut.dendrogram | General Tree Structures
cutree | Cut a Tree into Groups of Data
cycle | Sampling Times of Time Series

## -- D --

D | Symbolic and Algorithmic Derivatives of Simple Expressions
dbeta | The Beta Distribution
dbinom | The Binomial Distribution
dcauchy | The Cauchy Distribution
dchisq | The (non-central) Chi-Squared Distribution
decompose | Classical Seasonal Decomposition by Moving Averages
delete.response | Modify Terms Objects
deltat | Sampling Times of Time Series
dendrapply | Apply a Function to All Nodes of a Dendrogram
dendrogram | General Tree Structures
density | Kernel Density Estimation
deriv | Symbolic and Algorithmic Derivatives of Simple Expressions
deriv3 | Symbolic and Algorithmic Derivatives of Simple Expressions
deviance | Model Deviance
dexp | The Exponential Distribution
df | The F Distribution
df.kernel | Smoothing Kernel Objects
df.residual | Residual Degrees-of-Freedom
DF2formula | Model Formulae
dfbeta | Regression Deletion Diagnostics
dfbetas | Regression Deletion Diagnostics
dffits | Regression Deletion Diagnostics
dgamma | The Gamma Distribution
dgeom | The Geometric Distribution
dhyper | The Hypergeometric Distribution
diff.ts | Methods for Time Series Objects
diffinv | Discrete Integration: Inverse of Differencing
dist | Distance Matrix Computation
distribution | Distributions in the stats package
Distributions | Distributions in the stats package
distributions | Distributions in the stats package
dlnorm | The Log Normal Distribution
dlogis | The Logistic Distribution
dmultinom | The Multinomial Distribution
dnbinom | The Negative Binomial Distribution
dnorm | The Normal Distribution
dpois | The Poisson Distribution
drop.scope | Compute Allowed Changes in Adding to or Dropping from a Formula
drop.terms | Modify Terms Objects
drop1 | Add or Drop All Possible Single Terms to a Model
dsignrank | Distribution of the Wilcoxon Signed Rank Statistic
dt | The Student t Distribution
dummy.coef | Extract Coefficients in Original Coding
dummy.coef.lm | Extract Coefficients in Original Coding
dunif | The Uniform Distribution
dweibull | The Weibull Distribution
dwilcox | Distribution of the Wilcoxon Rank Sum Statistic

## -- E --

ecdf | Empirical Cumulative Distribution Function
eff.aovlist | Compute Efficiencies of Multistratum Analysis of Variance
effects | Effects from Fitted Model
embed | Embedding a Time Series
end | Encode the Terminal Times of Time Series
Error | Fit an Analysis of Variance Model
estVar | SSD Matrix and Estimated Variance Matrix in Multivariate Models
expand.model.frame | Add new variables to a model frame
Exponential | The Exponential Distribution
extractAIC | Extract AIC from a Fitted Model

## -- F --

factanal | Factor Analysis
factor.scope | Compute Allowed Changes in Adding to or Dropping from a Formula
family | Family Objects for Models
family.glm | Accessing Generalized Linear Model Fits
family.lm | Accessing Linear Model Fits
FDist | The F Distribution
fft | Fast Discrete Fourier Transform (FFT)
filter | Linear Filtering on a Time Series
fisher.test | Fisher's Exact Test for Count Data
fitted.kmeans | K-Means Clustering
fitted.values | Extract Model Fitted Values
fivenum | Tukey Five-Number Summaries
fligner.test | Fligner-Killeen Test of Homogeneity of Variances
format.dist | Distance Matrix Computation
format.ftable | Manipulate Flat Contingency Tables
formula | Model Formulae
formula.lm | Accessing Linear Model Fits
formula.nls | Extract Model Formula from nls Object
frequency | Sampling Times of Time Series
friedman.test | Friedman Rank Sum Test
ftable | Flat Contingency Tables
ftable.formula | Formula Notation for Flat Contingency Tables

## -- G --

Gamma | Family Objects for Models
GammaDist | The Gamma Distribution
gaussian | Family Objects for Models
Geometric | The Geometric Distribution
getCall | Update and Re-fit a Model Call
getInitial | Get Initial Parameter Estimates
get_all_vars | Extracting the Model Frame from a Formula or Fit
glm | Fitting Generalized Linear Models
glm.control | Auxiliary for Controlling GLM Fitting

## -- H --

hasTsp | Tsp Attribute of Time-Series-like Objects
hat | Regression Deletion Diagnostics
hatvalues | Regression Deletion Diagnostics
hclust | Hierarchical Clustering
heatmap | Draw a Heat Map
HoltWinters | Holt-Winters Filtering
Hypergeometric | The Hypergeometric Distribution

## -- I --

identify.hclust | Identify Clusters in a Dendrogram
influence | Regression Diagnostics
influence.measures | Regression Deletion Diagnostics
integrate | Integration of One-Dimensional Functions
interaction.plot | Two-way Interaction Plot
inverse.gaussian | Family Objects for Models
IQR | The Interquartile Range
is.empty.model | Test if a Model's Formula is Empty
is.leaf | General Tree Structures
is.mts | Time-Series Objects
is.stepfun | Step Functions - Creation and Class
is.ts | Time-Series Objects
is.tskernel | Smoothing Kernel Objects
isoreg | Isotonic / Monotone Regression

## -- K --

KalmanForecast | Kalman Filtering
KalmanLike | Kalman Filtering
KalmanRun | Kalman Filtering
KalmanSmooth | Kalman Filtering
kernapply | Apply Smoothing Kernel
kernel | Smoothing Kernel Objects
kmeans | K-Means Clustering
knots | Step Functions - Creation and Class
kruskal.test | Kruskal-Wallis Rank Sum Test
ks.test | Kolmogorov-Smirnov Tests
ksmooth | Kernel Regression Smoother

## -- L --

labels.dendrogram | Ordering or Labels of the Leaves in a Dendrogram
labels.dist | Distance Matrix Computation
labels.lm | Accessing Linear Model Fits
labels.terms | Model Terms
lag | Lag a Time Series
lag.plot | Time Series Lag Plots
line | Robust Line Fitting
lines.isoreg | Plot Method for isoreg Objects
lines.stepfun | Plot Step Functions
lines.ts | Plotting Time-Series Objects
listof | A Class for Lists of (Parts of) Model Fits
lm | Fitting Linear Models
lm.fit | Fitter Functions for Linear Models
lm.influence | Regression Diagnostics
lm.wfit | Fitter Functions for Linear Models
loadings | Print Loadings in Factor Analysis
loess | Local Polynomial Regression Fitting
loess.control | Set Parameters for Loess
loess.smooth | Scatter Plot with Smooth Curve Fitted by Loess
Logistic | The Logistic Distribution
logLik | Extract Log-Likelihood
loglin | Fitting Log-Linear Models
Lognormal | The Log Normal Distribution
lowess | Scatter Plot Smoothing
ls.diag | Compute Diagnostics for 'lsfit' Regression Results
ls.print | Print 'lsfit' Regression Results
lsfit | Find the Least Squares Fit

## -- M --

mad | Median Absolute Deviation
mahalanobis | Mahalanobis Distance
make.link | Create a Link for GLM Families
makeARIMA | Kalman Filtering
makepredictcall | Utility Function for Safe Prediction
makepredictcall.poly | Compute Orthogonal Polynomials
manova | Multivariate Analysis of Variance
mantelhaen.test | Cochran-Mantel-Haenszel Chi-Squared Test for Count Data
mauchly.test | Mauchly's Test of Sphericity
mcnemar.test | McNemar's Chi-squared Test for Count Data
median | Median Value
medpolish | Median Polish (Robust Twoway Decomposition) of a Matrix
merge.dendrogram | General Tree Structures
model.extract | Extract Components from a Model Frame
model.frame | Extracting the Model Frame from a Formula or Fit
model.matrix | Construct Design Matrices
model.offset | Extract Components from a Model Frame
model.response | Extract Components from a Model Frame
model.tables | Compute Tables of Results from an Aov Model Fit
model.weights | Extract Components from a Model Frame
monthplot | Plot a Seasonal or other Subseries from a Time Series
mood.test | Mood Two-Sample Test of Scale
Multinomial | The Multinomial Distribution
mvfft | Fast Discrete Fourier Transform (FFT)

## -- N --

na.action | NA Action
na.contiguous | Find Longest Contiguous Stretch of non-NAs
na.exclude | Handle Missing Values in Objects
na.fail | Handle Missing Values in Objects
na.omit | Handle Missing Values in Objects
na.omit.ts | Methods for Time Series Objects
na.pass | Handle Missing Values in Objects
napredict | Adjust for Missing Values
naprint | Adjust for Missing Values
naresid | Adjust for Missing Values
NegBinomial | The Negative Binomial Distribution
nextn | Find Highly Composite Numbers
nlm | Non-Linear Minimization
nlminb | Optimization using PORT routines
nls | Nonlinear Least Squares
nls.control | Control the Iterations in nls
NLSstAsymptotic | Fit the Asymptotic Regression Model
NLSstClosestX | Inverse Interpolation
NLSstLfAsymptote | Horizontal Asymptote on the Left Side
NLSstRtAsymptote | Horizontal Asymptote on the Right Side
nobs | Extract the Number of Observations from a Fit.
nobs.dendrogram | General Tree Structures
Normal | The Normal Distribution
numericDeriv | Evaluate Derivatives Numerically

## -- O --

offset | Include an Offset in a Model Formula
oneway.test | Test for Equal Means in a One-Way Layout
Ops.ts | Time-Series Objects
optim | General-purpose Optimization
optimHess | General-purpose Optimization
optimise | One Dimensional Optimization
optimize | One Dimensional Optimization
order.dendrogram | Ordering or Labels of the Leaves in a Dendrogram

## -- P --

p.adjust | Adjust P-values for Multiple Comparisons
p.adjust.methods | Adjust P-values for Multiple Comparisons
pacf | Auto- and Cross- Covariance and -Correlation Function Estimation
Pair | Construct paired-data object
pairwise.prop.test | Pairwise comparisons for proportions
pairwise.t.test | Pairwise t tests
pairwise.table | Tabulate p values for pairwise comparisons
pairwise.wilcox.test | Pairwise Wilcoxon Rank Sum Tests
pbeta | The Beta Distribution
pbinom | The Binomial Distribution
pbirthday | Probability of coincidences
pcauchy | The Cauchy Distribution
pchisq | The (non-central) Chi-Squared Distribution
pexp | The Exponential Distribution
pf | The F Distribution
pgamma | The Gamma Distribution
pgeom | The Geometric Distribution
phyper | The Hypergeometric Distribution
plnorm | The Log Normal Distribution
plogis | The Logistic Distribution
plot.acf | Plot Autocovariance and Autocorrelation Functions
plot.decomposed.ts | Classical Seasonal Decomposition by Moving Averages
plot.dendrogram | General Tree Structures
plot.density | Plot Method for Kernel Density Estimation
plot.ecdf | Empirical Cumulative Distribution Function
plot.hclust | Hierarchical Clustering
plot.HoltWinters | Plot function for HoltWinters objects
plot.isoreg | Plot Method for isoreg Objects
plot.lm | Plot Diagnostics for an lm Object
plot.ppr | Plot Ridge Functions for Projection Pursuit Regression Fit
plot.prcomp | Principal Components Analysis
plot.princomp | Principal Components Analysis
plot.profile.nls | Plot a profile.nls Object
plot.spec | Plotting Spectral Densities
plot.spec.coherency | Plotting Spectral Densities
plot.stepfun | Plot Step Functions
plot.stl | Methods for STL Objects
plot.ts | Plotting Time-Series Objects
plot.tskernel | Smoothing Kernel Objects
pnbinom | The Negative Binomial Distribution
pnorm | The Normal Distribution
Poisson | The Poisson Distribution
poisson | Family Objects for Models
poisson.test | Exact Poisson tests
poly | Compute Orthogonal Polynomials
polym | Compute Orthogonal Polynomials
power | Create a Power Link Object
power.anova.test | Power Calculations for Balanced One-Way Analysis of Variance Tests
power.prop.test | Power Calculations for Two-Sample Test for Proportions
power.t.test | Power calculations for one and two sample t tests
PP.test | Phillips-Perron Test for Unit Roots
ppoints | Ordinates for Probability Plotting
ppois | The Poisson Distribution
ppr | Projection Pursuit Regression
prcomp | Principal Components Analysis
predict | Model Predictions
predict.ar | Fit Autoregressive Models to Time Series
predict.Arima | Forecast from ARIMA fits
predict.arima0 | ARIMA Modelling of Time Series - Preliminary Version
predict.glm | Predict Method for GLM Fits
predict.HoltWinters | Prediction Function for Fitted Holt-Winters Models
predict.lm | Predict method for Linear Model Fits
predict.loess | Predict Loess Curve or Surface
predict.nls | Predicting from Nonlinear Least Squares Fits
predict.poly | Compute Orthogonal Polynomials
predict.prcomp | Principal Components Analysis
predict.princomp | Principal Components Analysis
predict.smooth.spline | Predict from Smoothing Spline Fit
predict.StructTS | Fit Structural Time Series
preplot | Pre-computations for a Plotting Object
princomp | Principal Components Analysis
print.aov | Fit an Analysis of Variance Model
print.ar | Fit Autoregressive Models to Time Series
print.arima0 | ARIMA Modelling of Time Series - Preliminary Version
print.dendrogram | General Tree Structures
print.dist | Distance Matrix Computation
print.ecdf | Empirical Cumulative Distribution Function
print.formula | Model Formulae
print.ftable | Manipulate Flat Contingency Tables
print.hclust | Hierarchical Clustering
print.HoltWinters | Holt-Winters Filtering
print.htest | Print Methods for Hypothesis Tests and Power Calculation Objects
print.integrate | Integration of One-Dimensional Functions
print.kmeans | K-Means Clustering
print.loadings | Print Loadings in Factor Analysis
print.power.htest | Print Methods for Hypothesis Tests and Power Calculation Objects
print.prcomp | Principal Components Analysis
print.princomp | Principal Components Analysis
print.stepfun | Step Functions - Creation and Class
print.StructTS | Fit Structural Time Series
print.summary.aov | Summarize an Analysis of Variance Model
print.summary.glm | Summarizing Generalized Linear Model Fits
print.summary.lm | Summarizing Linear Model Fits
print.summary.manova | Summary Method for Multivariate Analysis of Variance
print.summary.nls | Summarizing Non-Linear Least-Squares Model Fits
print.summary.prcomp | Principal Components Analysis
print.summary.princomp | Summary method for Principal Components Analysis
print.ts | Printing and Formatting of Time-Series Objects
print.xtabs | Cross Tabulation
printCoefmat | Print Coefficient Matrices
profile | Generic Function for Profiling Models
profile.nls | Method for Profiling nls Objects
proj | Projections of Models
promax | Rotation Methods for Factor Analysis
prop.test | Test of Equal or Given Proportions
prop.trend.test | Test for trend in proportions
psignrank | Distribution of the Wilcoxon Signed Rank Statistic
pt | The Student t Distribution
ptukey | The Studentized Range Distribution
punif | The Uniform Distribution
pweibull | The Weibull Distribution
pwilcox | Distribution of the Wilcoxon Rank Sum Statistic

## -- Q --

qbeta | The Beta Distribution
qbinom | The Binomial Distribution
qbirthday | Probability of coincidences
qcauchy | The Cauchy Distribution
qchisq | The (non-central) Chi-Squared Distribution
qexp | The Exponential Distribution
qf | The F Distribution
qgamma | The Gamma Distribution
qgeom | The Geometric Distribution
qhyper | The Hypergeometric Distribution
qlnorm | The Log Normal Distribution
qlogis | The Logistic Distribution
qnbinom | The Negative Binomial Distribution
qnorm | The Normal Distribution
qpois | The Poisson Distribution
qqline | Quantile-Quantile Plots
qqnorm | Quantile-Quantile Plots
qqplot | Quantile-Quantile Plots
qsignrank | Distribution of the Wilcoxon Signed Rank Statistic
qt | The Student t Distribution
qtukey | The Studentized Range Distribution
quade.test | Quade Test
quantile | Sample Quantiles
quantile.ecdf | Empirical Cumulative Distribution Function
quasi | Family Objects for Models
quasibinomial | Family Objects for Models
quasipoisson | Family Objects for Models
qunif | The Uniform Distribution
qweibull | The Weibull Distribution
qwilcox | Distribution of the Wilcoxon Rank Sum Statistic

## -- R --

r2dtable | Random 2-way Tables with Given Marginals
rbeta | The Beta Distribution
rbinom | The Binomial Distribution
rcauchy | The Cauchy Distribution
rchisq | The (non-central) Chi-Squared Distribution
read.ftable | Manipulate Flat Contingency Tables
rect.hclust | Draw Rectangles Around Hierarchical Clusters
reformulate | Modify Terms Objects
relevel | Reorder Levels of Factor
reorder | Reorder Levels of a Factor
reorder.dendrogram | Reorder a Dendrogram
replications | Number of Replications of Terms
reshape | Reshape Grouped Data
resid | Extract Model Residuals
residuals | Extract Model Residuals
residuals.glm | Accessing Generalized Linear Model Fits
residuals.HoltWinters | Holt-Winters Filtering
residuals.lm | Accessing Linear Model Fits
residuals.tukeyline | Robust Line Fitting
rev.dendrogram | General Tree Structures
rexp | The Exponential Distribution
rf | The F Distribution
rgamma | The Gamma Distribution
rgeom | The Geometric Distribution
rhyper | The Hypergeometric Distribution
rlnorm | The Log Normal Distribution
rlogis | The Logistic Distribution
rmultinom | The Multinomial Distribution
rnbinom | The Negative Binomial Distribution
rnorm | The Normal Distribution
rpois | The Poisson Distribution
rsignrank | Distribution of the Wilcoxon Signed Rank Statistic
rstandard | Regression Deletion Diagnostics
rstudent | Regression Deletion Diagnostics
rt | The Student t Distribution
runif | The Uniform Distribution
runmed | Running Medians - Robust Scatter Plot Smoothing
rweibull | The Weibull Distribution
rwilcox | Distribution of the Wilcoxon Rank Sum Statistic
rWishart | Random Wishart Distributed Matrices

## -- S --

SafePrediction | Utility Function for Safe Prediction
scatter.smooth | Scatter Plot with Smooth Curve Fitted by Loess
screeplot | Screeplots
sd | Standard Deviation
se.contrast | Standard Errors for Contrasts in Model Terms
se.contrast.aov | Standard Errors for Contrasts in Model Terms
selfStart | Construct Self-starting Nonlinear Models
setNames | Set the Names in an Object
shapiro.test | Shapiro-Wilk Normality Test
sigma | Extract Residual Standard Deviation 'Sigma'
SignRank | Distribution of the Wilcoxon Signed Rank Statistic
simulate | Simulate Responses
smooth | Tukey's (Running Median) Smoothing
smooth.spline | Fit a Smoothing Spline
smoothEnds | End Points Smoothing (for Running Medians)
sortedXyData | Create a 'sortedXyData' Object
spec | Spectral Density Estimation
spec.ar | Estimate Spectral Density of a Time Series from AR Fit
spec.pgram | Estimate Spectral Density of a Time Series by a Smoothed Periodogram
spec.taper | Taper a Time Series by a Cosine Bell
spectrum | Spectral Density Estimation
spline | Interpolating Splines
splinefun | Interpolating Splines
splinefunH | Interpolating Splines
SSasymp | Self-Starting Nls Asymptotic Regression Model
SSasympOff | Self-Starting Nls Asymptotic Regression Model with an Offset
SSasympOrig | Self-Starting Nls Asymptotic Regression Model through the Origin
SSbiexp | Self-Starting Nls Biexponential model
SSD | SSD Matrix and Estimated Variance Matrix in Multivariate Models
SSfol | Self-Starting Nls First-order Compartment Model
SSfpl | Self-Starting Nls Four-Parameter Logistic Model
SSgompertz | Self-Starting Nls Gompertz Growth Model
SSlogis | Self-Starting Nls Logistic Model
SSmicmen | Self-Starting Nls Michaelis-Menten Model
SSweibull | Self-Starting Nls Weibull Growth Curve Model
start | Encode the Terminal Times of Time Series
stat.anova | GLM Anova Statistics
stats | The R Stats Package
stats-deprecated | Deprecated Functions in Package 'stats'
step | Choose a model by AIC in a Stepwise Algorithm
stepfun | Step Functions - Creation and Class
stl | Seasonal Decomposition of Time Series by Loess
str.dendrogram | General Tree Structures
StructTS | Fit Structural Time Series
summary.aov | Summarize an Analysis of Variance Model
summary.ecdf | Empirical Cumulative Distribution Function
summary.glm | Summarizing Generalized Linear Model Fits
summary.lm | Summarizing Linear Model Fits
summary.manova | Summary Method for Multivariate Analysis of Variance
summary.nls | Summarizing Non-Linear Least-Squares Model Fits
summary.prcomp | Principal Components Analysis
summary.princomp | Summary method for Principal Components Analysis
summary.stepfun | Step Functions - Creation and Class
supsmu | Friedman's SuperSmoother
symnum | Symbolic Number Coding

## -- T --

t.test | Student's t-Test
t.ts | Time-Series Objects
TDist | The Student t Distribution
termplot | Plot Regression Terms
terms | Model Terms
terms.formula | Construct a terms Object from a Formula
terms.object | Description of Terms Objects
time | Sampling Times of Time Series
time.default | Sampling Times of Time Series
toeplitz | Form Symmetric Toeplitz Matrix
ts | Time-Series Objects
ts.intersect | Bind Two or More Time Series
ts.plot | Plot Multiple Time Series
ts.union | Bind Two or More Time Series
tsdiag | Diagnostic Plots for Time-Series Fits
tsp | Tsp Attribute of Time-Series-like Objects
tsSmooth | Use Fixed-Interval Smoothing on Time Series
Tukey | The Studentized Range Distribution
TukeyHSD | Compute Tukey Honest Significant Differences

## -- U --

Uniform | The Uniform Distribution
uniroot | One Dimensional Root (Zero) Finding
update | Update and Re-fit a Model Call
update.formula | Model Updating

## -- V --

var | Correlation, Variance and Covariance (Matrices)
var.test | F Test to Compare Two Variances
variable.names | Case and Variable Names of Fitted Models
variable.names.lm | Case and Variable Names of Fitted Models
varimax | Rotation Methods for Factor Analysis
vcov | Calculate Variance-Covariance Matrix for a Fitted Model Object
vcov.lme | Calculate Variance-Covariance Matrix for a Fitted Model Object
vcov.summary.lm | Calculate Variance-Covariance Matrix for a Fitted Model Object

## -- W --

Weibull | The Weibull Distribution
weighted.mean | Weighted Arithmetic Mean
weighted.mean.default | Weighted Arithmetic Mean
weighted.residuals | Compute Weighted Residuals
weights | Extract Model Weights
weights.glm | Fitting Generalized Linear Models
wilcox.test | Wilcoxon Rank Sum and Signed Rank Tests
Wilcoxon | Distribution of the Wilcoxon Rank Sum Statistic
window | Time (Series) Windows
write.ftable | Manipulate Flat Contingency Tables

## -- X --

xtabs | Cross Tabulation

## -- misc --

.checkMFClasses | Functions to Check the Type of Variables passed to Model Frames
.getXlevels | Functions to Check the Type of Variables passed to Model Frames
.lm.fit | Fitter Functions for Linear Models
.MFclass | Functions to Check the Type of Variables passed to Model Frames
.nknots.smspl | Fit a Smoothing Spline
.preformat.ts | Printing and Formatting of Time-Series Objects
.vcov.aliased | Calculate Variance-Covariance Matrix for a Fitted Model Object
[.acf | Auto- and Cross- Covariance and -Correlation Function Estimation
[.formula | Model Formulae
[.terms | Modify Terms Objects
[.ts | Time-Series Objects
[[.dendrogram | General Tree Structures