# 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 | |

No Results! |

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