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 | 
| 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 | 
| 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 | 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 | 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 | 
| 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 | 
| 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 | 
| 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 | 
| 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 | 
| 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 | 
| 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 | 
| 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 | 
| 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 | 
| 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) | 
| 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 | 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 | 
| 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.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 | 
| 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 | 
| plclust | Deprecated Functions in Package 'stats' | 
| 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 | 
| 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 | 
| 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 | 
| 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.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 | 
| Uniform | The Uniform Distribution | 
| uniroot | One Dimensional Root (Zero) Finding | 
| update | Update and Re-fit a Model Call | 
| update.formula | Model Updating | 
| 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 | 
| 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 Windows | 
| write.ftable | Manipulate Flat Contingency Tables | 
| xtabs | Cross Tabulation | 
| .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 |