sd: Standard Deviation

stats

acf: Auto- and Cross- Covariance and -Correlation Function... acf2AR: Compute an AR Process Exactly Fitting an ACF 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 approxfun: Interpolation Functions ar: Fit Autoregressive Models to Time Series arima: ARIMA Modelling of Time Series arima0: ARIMA Modelling of Time Series - Preliminary Version arima.sim: Simulate from an ARIMA Model ARMAacf: Compute Theoretical ACF for an ARMA Process ARMAtoMA: Convert ARMA Process to Infinite MA Process ar.ols: Fit Autoregressive Models to Time Series by OLS as.hclust: Convert Objects to Class hclust asOneSidedFormula: Convert to One-Sided Formula ave: Group Averages Over Level Combinations of Factors bandwidth: Bandwidth Selectors for Kernel Density Estimation bartlett.test: Bartlett Test of Homogeneity of Variances Beta: The Beta Distribution Binomial: The Binomial Distribution binom.test: Exact Binomial Test biplot: Biplot of Multivariate Data biplot.princomp: Biplot for Principal Components birthday: Probability of coincidences box.test: Box-Pierce and Ljung-Box Tests cancor: Canonical Correlations case.names: Case and Variable Names of Fitted Models Cauchy: The Cauchy Distribution checkMFClasses: Functions to Check the Type of Variables passed to Model... 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 complete.cases: Find Complete Cases confint: Confidence Intervals for Model Parameters constrOptim: Linearly Constrained Optimization contrast: (Possibly Sparse) Contrast Matrices contrasts: Get and Set Contrast Matrices convolve: Convolution of Sequences via FFT cophenetic: Cophenetic Distances for a Hierarchical Clustering cor: Correlation, Variance and Covariance (Matrices) cor.test: Test for Association/Correlation Between Paired Samples cov.wt: Weighted Covariance Matrices cpgram: Plot Cumulative Periodogram cutree: Cut a Tree into Groups of Data decompose: Classical Seasonal Decomposition by Moving Averages delete.response: Modify Terms Objects 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 deviance: Model Deviance df.residual: Residual Degrees-of-Freedom diffinv: Discrete Integration: Inverse of Differencing dist: Distance Matrix Computation Distributions: Distributions in the stats package dummy.coef: Extract Coefficients in Original Coding ecdf: Empirical Cumulative Distribution Function eff.aovlist: Compute Efficiencies of Multistratum Analysis of Variance effects: Effects from Fitted Model embed: Embedding a Time Series 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... family: Family Objects for Models 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.values: Extract Model Fitted Values fivenum: Tukey Five-Number Summaries fligner.test: Fligner-Killeen Test of Homogeneity of Variances formula: Model Formulae formula.nls: Extract Model Formula from nls Object friedman.test: Friedman Rank Sum Test ftable: Flat Contingency Tables ftable.formula: Formula Notation for Flat Contingency Tables GammaDist: The Gamma Distribution Geometric: The Geometric Distribution getInitial: Get Initial Parameter Estimates glm: Fitting Generalized Linear Models glm.control: Auxiliary for Controlling GLM Fitting glm.summaries: Accessing Generalized Linear Model Fits hclust: Hierarchical Clustering heatmap: Draw a Heat Map HoltWinters: Holt-Winters Filtering Hypergeometric: The Hypergeometric Distribution identify.hclust: Identify Clusters in a Dendrogram influence.measures: Regression Deletion Diagnostics integrate: Integration of One-Dimensional Functions interaction.plot: Two-way Interaction Plot IQR: The Interquartile Range is.empty: Test if a Model's Formula is Empty isoreg: Isotonic / Monotone Regression KalmanLike: Kalman Filtering kernapply: Apply Smoothing Kernel kernel: Smoothing Kernel Objects kmeans: K-Means Clustering kruskal.test: Kruskal-Wallis Rank Sum Test ksmooth: Kernel Regression Smoother ks.test: Kolmogorov-Smirnov Tests lag: Lag a Time Series lag.plot: Time Series Lag Plots line: Robust Line Fitting listof: A Class for Lists of (Parts of) Model Fits lm: Fitting Linear Models lmfit: Fitter Functions for Linear Models lm.influence: Regression Diagnostics lm.summaries: Accessing Linear Model Fits loadings: Print Loadings in Factor Analysis loess: Local Polynomial Regression Fitting loess.control: Set Parameters for 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 lsfit: Find the Least Squares Fit ls.print: Print 'lsfit' Regression Results mad: Median Absolute Deviation mahalanobis: Mahalanobis Distance make.link: Create a Link for GLM Families makepredictcall: Utility Function for Safe Prediction 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 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.tables: Compute Tables of Results from an Aov Model Fit monthplot: Plot a Seasonal or other Subseries from a Time Series mood.test: Mood Two-Sample Test of Scale Multinom: The Multinomial Distribution na.action: NA Action na.contiguous: Find Longest Contiguous Stretch of non-NAs na.fail: Handle Missing Values in Objects nafns: Adjust for Missing Values naprint: 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. 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 optim: General-purpose Optimization optimize: One Dimensional Optimization order.dendrogram: Ordering or Labels of the Leaves in a Dendrogram p.adjust: Adjust P-values for Multiple Comparisons Pair: Construct paired-data object pairwise.prop.test: Pairwise comparisons for proportions pairwise.table: Tabulate p values for pairwise comparisons pairwise.t.test: Pairwise t tests pairwise.wilcox.test: Pairwise Wilcoxon Rank Sum Tests plot.acf: Plot Autocovariance and Autocorrelation Functions plot.density: Plot Method for Kernel Density Estimation 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.profile.nls: Plot a profile.nls Object plot.spec: Plotting Spectral Densities plot.stepfun: Plot Step Functions plot.ts: Plotting Time-Series Objects Poisson: The Poisson Distribution poisson.test: Exact Poisson tests poly: Compute Orthogonal Polynomials power: Create a Power Link Object power.anova.test: Power Calculations for Balanced One-Way Analysis of Variance... power.prop.test: Power Calculations for Two-Sample Test for Proportions power.t.test: Power calculations for one and two sample t tests ppoints: Ordinates for Probability Plotting ppr: Projection Pursuit Regression pp.test: Phillips-Perron Test for Unit Roots prcomp: Principal Components Analysis predict: Model Predictions predict.arima: Forecast from ARIMA fits 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.smooth.spline: Predict from Smoothing Spline Fit preplot: Pre-computations for a Plotting Object princomp: Principal Components Analysis printCoefmat: Print Coefficient Matrices print.power.htest: Print Methods for Hypothesis Tests and Power Calculation... print.ts: Printing and Formatting of Time-Series Objects profile: Generic Function for Profiling Models profile.nls: Method for Profiling nls Objects proj: Projections of Models prop.test: Test of Equal or Given Proportions prop.trend.test: Test for trend in proportions qqnorm: Quantile-Quantile Plots quade.test: Quade Test quantile: Sample Quantiles r2dtable: Random 2-way Tables with Given Marginals read.ftable: Manipulate Flat Contingency Tables rect.hclust: Draw Rectangles Around Hierarchical Clusters relevel: Reorder Levels of Factor reorder.dendrogram: Reorder a Dendrogram reorder.factor: Reorder Levels of a Factor replications: Number of Replications of Terms reshape: Reshape Grouped Data residuals: Extract Model Residuals runmed: Running Medians - Robust Scatter Plot Smoothing rWishart: Random Wishart Distributed Matrices scatter.smooth: Scatter Plot with Smooth Curve Fitted by Loess screeplot: Screeplots sd: Standard Deviation se.contrast: 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 smoothEnds: End Points Smoothing (for Running Medians) smooth.spline: Fit a Smoothing Spline sortedXyData: Create a 'sortedXyData' Object spec.ar: Estimate Spectral Density of a Time Series from AR Fit spec.pgram: Estimate Spectral Density of a Time Series by a Smoothed... spec.taper: Taper a Time Series by a Cosine Bell spectrum: Spectral Density Estimation splinefun: 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... SSbiexp: Self-Starting Nls Biexponential model SSD: SSD Matrix and Estimated Variance Matrix in Multivariate... 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-defunct: Defunct Functions in Package 'stats' stats-deprecated: Deprecated Functions in Package 'stats' stats-package: The R Stats Package step: Choose a model by AIC in a Stepwise Algorithm stepfun: Step Functions - Creation and Class stl: Seasonal Decomposition of Time Series by Loess stlmethods: Methods for STL Objects StructTS: Fit Structural Time Series summary.aov: Summarize an Analysis of Variance Model 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.princomp: Summary method for Principal Components Analysis supsmu: Friedman's SuperSmoother symnum: Symbolic Number Coding 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 toeplitz: Form Symmetric Toeplitz Matrix ts: Time-Series Objects tsdiag: Diagnostic Plots for Time-Series Fits ts-methods: Methods for Time Series Objects tsp: Tsp Attribute of Time-Series-like Objects ts.plot: Plot Multiple Time Series tsSmooth: Use Fixed-Interval Smoothing on Time Series ts.union: Bind Two or More Time Series t.test: Student's t-Test 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 varimax: Rotation Methods for Factor Analysis var.test: F Test to Compare Two Variances vcov: Calculate Variance-Covariance Matrix for a Fitted Model... Weibull: The Weibull Distribution weighted.mean: Weighted Arithmetic Mean weighted.residuals: Compute Weighted Residuals weights: Extract Model Weights Wilcoxon: Distribution of the Wilcoxon Rank Sum Statistic wilcox.test: Wilcoxon Rank Sum and Signed Rank Tests window: Time (Series) Windows xtabs: Cross Tabulation zC: Sets Contrasts for a Factor