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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