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stats (version 3.6.2)
The R Stats Package
Description
R statistical functions.
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3.6.2
3.6.1
3.6.0
3.5.3
3.5.2
3.5.1
3.5.0
3.4.3
3.4.1
3.4.0
3.3.3
3.3.2
3.3.1
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3.2.5
3.2.4
3.2.2
3.2.1
3.1.3
3.1.2
3.1.1
@VERSION@
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Version
3.6.2
License
Part of R 3.6.2
Maintainer
R-core R-core@R-project.org
Last Published
January 1st, 1970
Functions in stats (3.6.2)
Search functions
FDist
The F Distribution
ARMAacf
Compute Theoretical ACF for an ARMA Process
AIC
Akaike's An Information Criterion
HoltWinters
Holt-Winters Filtering
Hypergeometric
The Hypergeometric Distribution
IQR
The Interquartile Range
KalmanLike
Kalman Filtering
Binomial
The Binomial Distribution
Cauchy
The Cauchy Distribution
NLSstClosestX
Inverse Interpolation
NLSstLfAsymptote
Horizontal Asymptote on the Left Side
Normal
The Normal Distribution
Poisson
The Poisson Distribution
Logistic
The Logistic Distribution
Lognormal
The Log Normal Distribution
SSweibull
Self-Starting Nls Weibull Growth Curve Model
SignRank
Distribution of the Wilcoxon Signed Rank Statistic
NLSstRtAsymptote
Horizontal Asymptote on the Right Side
NegBinomial
The Negative Binomial Distribution
Distributions
Distributions in the stats package
Chisquare
The (non-central) Chi-Squared Distribution
SSmicmen
Self-Starting Nls Michaelis-Menten Model
SSlogis
Self-Starting Nls Logistic Model
ARMAtoMA
Convert ARMA Process to Infinite MA Process
Beta
The Beta Distribution
NLSstAsymptotic
Fit the Asymptotic Regression Model
Multinom
The Multinomial Distribution
SSasymp
Self-Starting Nls Asymptotic Regression Model
SSD
SSD Matrix and Estimated Variance Matrix in Multivariate Models
Tukey
The Studentized Range Distribution
SSfpl
Self-Starting Nls Four-Parameter Logistic Model
SSgompertz
Self-Starting Nls Gompertz Growth Model
TukeyHSD
Compute Tukey Honest Significant Differences
GammaDist
The Gamma Distribution
Geometric
The Geometric Distribution
aggregate
Compute Summary Statistics of Data Subsets
addmargins
Puts Arbitrary Margins on Multidimensional Tables or Arrays
TDist
The Student t Distribution
StructTS
Fit Structural Time Series
SSasympOrig
Self-Starting Nls Asymptotic Regression Model through the Origin
SSasympOff
Self-Starting Nls Asymptotic Regression Model with an Offset
Uniform
The Uniform Distribution
anova.mlm
Comparisons between Multivariate Linear Models
alias
Find Aliases (Dependencies) in a Model
SSbiexp
Self-Starting Nls Biexponential model
ansari.test
Ansari-Bradley Test
Weibull
The Weibull Distribution
binom.test
Exact Binomial Test
SSfol
Self-Starting Nls First-order Compartment Model
chisq.test
Pearson's Chi-squared Test for Count Data
acf
Auto- and Cross- Covariance and -Correlation Function Estimation
biplot
Biplot of Multivariate Data
Wilcoxon
Distribution of the Wilcoxon Rank Sum Statistic
acf2AR
Compute an AR Process Exactly Fitting an ACF
cmdscale
Classical (Metric) Multidimensional Scaling
add1
Add or Drop All Possible Single Terms to a Model
anova.glm
Analysis of Deviance for Generalized Linear Model Fits
ar.ols
Fit Autoregressive Models to Time Series by OLS
ave
Group Averages Over Level Combinations of Factors
asOneSidedFormula
Convert to One-Sided Formula
ar
Fit Autoregressive Models to Time Series
Box.test
Box-Pierce and Ljung-Box Tests
cancor
Canonical Correlations
bandwidth
Bandwidth Selectors for Kernel Density Estimation
coef
Extract Model Coefficients
convolve
Convolution of Sequences via FFT
anova
Anova Tables
bartlett.test
Bartlett Test of Homogeneity of Variances
complete.cases
Find Complete Cases
cophenetic
Cophenetic Distances for a Hierarchical Clustering
aov
Fit an Analysis of Variance Model
arima0
ARIMA Modelling of Time Series -- Preliminary Version
approxfun
Interpolation Functions
case+variable.names
Case and Variable Names of Fitted Models
arima.sim
Simulate from an ARIMA Model
anova.lm
ANOVA for Linear Model Fits
.checkMFClasses
Functions to Check the Type of Variables passed to Model Frames
arima
ARIMA Modelling of Time Series
as.hclust
Convert Objects to Class hclust
cov.wt
Weighted Covariance Matrices
cpgram
Plot Cumulative Periodogram
cutree
Cut a Tree into Groups of Data
dendrogram
General Tree Structures
confint
Confidence Intervals for Model Parameters
biplot.princomp
Biplot for Principal Components
birthday
Probability of coincidences
density
Kernel Density Estimation
contrasts
Get and Set Contrast Matrices
df.residual
Residual Degrees-of-Freedom
contrast
(Possibly Sparse) Contrast Matrices
diffinv
Discrete Integration: Inverse of Differencing
constrOptim
Linearly Constrained Optimization
decompose
Classical Seasonal Decomposition by Moving Averages
factanal
Factor Analysis
factor.scope
Compute Allowed Changes in Adding to or Dropping from a Formula
cor
Correlation, Variance and Covariance (Matrices)
cor.test
Test for Association/Correlation Between Paired Samples
dist
Distance Matrix Computation
dummy.coef
Extract Coefficients in Original Coding
fivenum
Tukey Five-Number Summaries
fitted
Extract Model Fitted Values
influence.measures
Regression Deletion Diagnostics
delete.response
Modify Terms Objects
kmeans
K-Means Clustering
identify.hclust
Identify Clusters in a Dendrogram
model.frame
Extracting the Model Frame from a Formula or Fit
model.matrix
Construct Design Matrices
deriv
Symbolic and Algorithmic Derivatives of Simple Expressions
ecdf
Empirical Cumulative Distribution Function
effects
Effects from Fitted Model
embed
Embedding a Time Series
deviance
Model Deviance
eff.aovlist
Compute Efficiencies of Multistratum Analysis of Variance
filter
Linear Filtering on a Time Series
fligner.test
Fligner-Killeen Test of Homogeneity of Variances
formula
Model Formulae
family
Family Objects for Models
fft
Fast Discrete Fourier Transform (FFT)
dendrapply
Apply a Function to All Nodes of a Dendrogram
ftable
Flat Contingency Tables
glm
Fitting Generalized Linear Models
ls.print
Print
lsfit
Regression Results
ftable.formula
Formula Notation for Flat Contingency Tables
ks.test
Kolmogorov-Smirnov Tests
fisher.test
Fisher's Exact Test for Count Data
getInitial
Get Initial Parameter Estimates
expand.model.frame
Add new variables to a model frame
extractAIC
Extract AIC from a Fitted Model
lag.plot
Time Series Lag Plots
kernapply
Apply Smoothing Kernel
kernel
Smoothing Kernel Objects
model.extract
Extract Components from a Model Frame
make.link
Create a Link for GLM Families
medpolish
Median Polish (Robust Twoway Decomposition) of a Matrix
mahalanobis
Mahalanobis Distance
na.contiguous
Find Longest Contiguous Stretch of non-NAs
lag
Lag a Time Series
power.anova.test
Power Calculations for Balanced One-Way Analysis of Variance Tests
formula.nls
Extract Model Formula from nls Object
friedman.test
Friedman Rank Sum Test
heatmap
Draw a Heat Map
hclust
Hierarchical Clustering
mad
Median Absolute Deviation
loadings
Print Loadings in Factor Analysis
lsfit
Find the Least Squares Fit
integrate
Integration of One-Dimensional Functions
na.fail
Handle Missing Values in Objects
line
Robust Line Fitting
isoreg
Isotonic / Monotone Regression
kruskal.test
Kruskal-Wallis Rank Sum Test
oneway.test
Test for Equal Means in a One-Way Layout
optim
General-purpose Optimization
glm.summaries
Accessing Generalized Linear Model Fits
glm.control
Auxiliary for Controlling GLM Fitting
ksmooth
Kernel Regression Smoother
loess
Local Polynomial Regression Fitting
order.dendrogram
Ordering or Labels of the Leaves in a Dendrogram
PP.test
Phillips-Perron Test for Unit Roots
interaction.plot
Two-way Interaction Plot
na.action
NA Action
listof
A Class for Lists of (Parts of) Model Fits
pairwise.prop.test
Pairwise comparisons for proportions
prop.trend.test
Test for trend in proportions
p.adjust
Adjust P-values for Multiple Comparisons
preplot
Pre-computations for a Plotting Object
poly
Compute Orthogonal Polynomials
is.empty.model
Test if a Model's Formula is Empty
lm.summaries
Accessing Linear Model Fits
loess.control
Set Parameters for Loess
naresid
Adjust for Missing Values
numericDeriv
Evaluate Derivatives Numerically
lm
Fitting Linear Models
ls.diag
Compute Diagnostics for
lsfit
Regression Results
lm.fit
Fitter Functions for Linear Models
optimize
One Dimensional Optimization
mcnemar.test
McNemar's Chi-squared Test for Count Data
loglin
Fitting Log-Linear Models
power
Create a Power Link Object
predict.Arima
Forecast from ARIMA fits
predict
Model Predictions
lowess
Scatter Plot Smoothing
predict.smooth.spline
Predict from Smoothing Spline Fit
model.tables
Compute Tables of Results from an Aov Model Fit
mauchly.test
Mauchly's Test of Sphericity
mantelhaen.test
Cochran-Mantel-Haenszel Chi-Squared Test for Count Data
logLik
Extract Log-Likelihood
plot.acf
Plot Autocovariance and Autocorrelation Functions
median
Median Value
se.contrast
Standard Errors for Contrasts in Model Terms
mood.test
Mood Two-Sample Test of Scale
monthplot
Plot a Seasonal or other Subseries from a Time Series
selfStart
Construct Self-starting Nonlinear Models
lm.influence
Regression Diagnostics
qqnorm
Quantile-Quantile Plots
naprint
Adjust for Missing Values
manova
Multivariate Analysis of Variance
offset
Include an Offset in a Model Formula
makepredictcall
Utility Function for Safe Prediction
poisson.test
Exact Poisson tests
smoothEnds
End Points Smoothing (for Running Medians)
predict.glm
Predict Method for GLM Fits
reorder.default
Reorder Levels of a Factor
plot.density
Plot Method for Kernel Density Estimation
nextn
Find Highly Composite Numbers
pairwise.wilcox.test
Pairwise Wilcoxon Rank Sum Tests
nlm
Non-Linear Minimization
nobs
Extract the Number of Observations from a Fit.
nls.control
Control the Iterations in nls
plot.isoreg
Plot Method for isoreg Objects
power.prop.test
Power Calculations for Two-Sample Test for Proportions
rWishart
Random Wishart Distributed Matrices
replications
Number of Replications of Terms
profile.nls
Method for Profiling nls Objects
plot.lm
Plot Diagnostics for an lm Object
prcomp
Principal Components Analysis
predict.HoltWinters
Prediction Function for Fitted Holt-Winters Models
plot.ts
Plotting Time-Series Objects
pairwise.table
Tabulate p values for pairwise comparisons
sortedXyData
Create a
sortedXyData
Object
predict.loess
Predict Loess Curve or Surface
power.t.test
Power calculations for one and two sample t tests
plot.stepfun
Plot Step Functions
pairwise.t.test
Pairwise t tests
nls
Nonlinear Least Squares
r2dtable
Random 2-way Tables with Given Marginals
summary.nls
Summarizing Non-Linear Least-Squares Model Fits
spec.taper
Taper a Time Series by a Cosine Bell
supsmu
Friedman's SuperSmoother
spectrum
Spectral Density Estimation
quade.test
Quade Test
plot.spec
Plotting Spectral Densities
plot.HoltWinters
Plot function for HoltWinters objects
print.ts
Printing and Formatting of Time-Series Objects
varimax
Rotation Methods for Factor Analysis
relevel
Reorder Levels of Factor
reshape
Reshape Grouped Data
princomp
Principal Components Analysis
ppr
Projection Pursuit Regression
ppoints
Ordinates for Probability Plotting
summary.lm
Summarizing Linear Model Fits
proj
Projections of Models
terms.object
Description of Terms Objects
print.power.htest
Print Methods for Hypothesis Tests and Power Calculation Objects
smooth.spline
Fit a Smoothing Spline
summary.manova
Summary Method for Multivariate Analysis of Variance
quantile
Sample Quantiles
smooth
Tukey's (Running Median) Smoothing
nlminb
Optimization using PORT routines
printCoefmat
Print Coefficient Matrices
runmed
Running Medians -- Robust Scatter Plot Smoothing
tsdiag
Diagnostic Plots for Time-Series Fits
residuals
Extract Model Residuals
splinefun
Interpolating Splines
time
Sampling Times of Time Series
start
Encode the Terminal Times of Time Series
window
Time Windows
predict.nls
Predicting from Nonlinear Least Squares Fits
summary.princomp
Summary method for Principal Components Analysis
plot.profile.nls
Plot a profile.nls Object
scatter.smooth
Scatter Plot with Smooth Curve Fitted by Loess
stats-defunct
Defunct Functions in Package
stats
simulate
Simulate Responses
sigma
Extract Residual Standard Deviation 'Sigma'
prop.test
Test of Equal or Given Proportions
stat.anova
GLM Anova Statistics
plot.ppr
Plot Ridge Functions for Projection Pursuit Regression Fit
read.ftable
Manipulate Flat Contingency Tables
profile
Generic Function for Profiling Models
predict.lm
Predict method for Linear Model Fits
weighted.mean
Weighted Arithmetic Mean
tsp
Tsp Attribute of Time-Series-like Objects
t.test
Student's t-Test
screeplot
Screeplots
update.formula
Model Updating
ts.union
Bind Two or More Time Series
stats-deprecated
Deprecated Functions in Package
stats
rect.hclust
Draw Rectangles Around Hierarchical Clusters
xtabs
Cross Tabulation
symnum
Symbolic Number Coding
stlmethods
Methods for STL Objects
stl
Seasonal Decomposition of Time Series by Loess
terms
Model Terms
terms.formula
Construct a terms Object from a Formula
ts
Time-Series Objects
C
Sets Contrasts for a Factor
ts.plot
Plot Multiple Time Series
var.test
F Test to Compare Two Variances
weights
Extract Model Weights
reorder.dendrogram
Reorder a Dendrogram
stepfun
Step Functions - Creation and Class
vcov
Calculate Variance-Covariance Matrix for a Fitted Model Object
setNames
Set the Names in an Object
toeplitz
Form Symmetric Toeplitz Matrix
spec.pgram
Estimate Spectral Density of a Time Series by a Smoothed Periodogram
step
Choose a model by AIC in a Stepwise Algorithm
spec.ar
Estimate Spectral Density of a Time Series from AR Fit
summary.glm
Summarizing Generalized Linear Model Fits
sd
Standard Deviation
tsSmooth
Use Fixed-Interval Smoothing on Time Series
termplot
Plot Regression Terms
summary.aov
Summarize an Analysis of Variance Model
shapiro.test
Shapiro-Wilk Normality Test
stats-package
The R Stats Package
ts-methods
Methods for Time Series Objects
update
Update and Re-fit a Model Call
uniroot
One Dimensional Root (Zero) Finding
wilcox.test
Wilcoxon Rank Sum and Signed Rank Tests
weighted.residuals
Compute Weighted Residuals
Exponential
The Exponential Distribution