stats v3.6.2
The R Stats Package
R statistical functions.
Functions in stats
Name | Description | |
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 | |
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