The R Stats Package
![[R logo]](../../../doc/html/Rlogo.svg)
![[Up]](../../../doc/html/left.jpg)
![[Top]](../../../doc/html/up.jpg)
Documentation for package ‘stats’ version 4.5.0
- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- 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 | \IBox-\IPierce and \ILjung-\IBox 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 |
| head.ts | Time-Series Objects |
| 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 | \IMauchly's Test of Sphericity |
| mcnemar.test | McNemar's Chi-squared Test for Count Data |
| median | Median Value |
| medpolish | Median Polish (Robust Two-way 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 a Paired-Data Object |
| pairs.profile | Plotting Functions for 'profile' Objects |
| 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 | Plotting Functions for 'profile' Objects |
| 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.lm | Fitting Linear Models |
| 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.glm | Method for Profiling 'glm' Objects |
| 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 |
| psmirnov | Distribution of the Smirnov 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 |
| qr.influence | Regression Diagnostics |
| qsignrank | Distribution of the Wilcoxon Signed Rank Statistic |
| qsmirnov | Distribution of the Smirnov 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.default | 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 |
| rsmirnov | Distribution of the Smirnov 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 | Scree Plots |
| 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 |
| Smirnov | Distribution of the Smirnov Statistic |
| 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 Model |
| SSasympOff | Self-Starting 'nls' Asymptotic Model with an Offset |
| SSasympOrig | Self-Starting 'nls' Asymptotic 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 |
| tail.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 | Create Symmetric and Asymmetric Toeplitz Matrix |
| toeplitz2 | Create Symmetric and Asymmetric 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 |