Learn R Programming

⚠️There's a newer version (3.6.2) of this package.Take me there.

stats (version 3.2.1)

The R Stats Package

Description

R statistical functions.

Copy Link

Version

Version

3.2.1

License

Part of R 3.2.1

Maintainer

R-core R-core@R-project.org

Last Published

December 12th, 2019

Functions in stats (3.2.1)

ANOVA for Linear Model Fits

Auto- and Cross- Covariance and -Correlation Function Estimation

Akaike's An Information Criterion

Analysis of Deviance for Generalized Linear Model Fits

Find Aliases (Dependencies) in a Model

Compute an AR Process Exactly Fitting an ACF

Add or Drop All Possible Single Terms to a Model

Compute Summary Statistics of Data Subsets

Puts Arbitrary Margins on Multidimensional Tables or Arrays

Simulate from an ARIMA Model

Fit Autoregressive Models to Time Series

Fit an Analysis of Variance Model

Ansari-Bradley Test

Interpolation Functions

ARIMA Modelling of Time Series

ARIMA Modelling of Time Series -- Preliminary Version

Compute Theoretical ACF for an ARMA Process

Fit Autoregressive Models to Time Series by OLS

Comparisons between Multivariate Linear Models

Convert ARMA Process to Infinite MA Process

Group Averages Over Level Combinations of Factors

Bartlett Test of Homogeneity of Variances

Exact Binomial Test

Bandwidth Selectors for Kernel Density Estimation

Convert Objects to Class hclust

asOneSidedFormula

Convert to One-Sided Formula

Biplot of Multivariate Data

The Binomial Distribution

The Beta Distribution

Probability of coincidences

.checkMFClasses

Functions to Check the Type of Variables passed to Model Frames

Box-Pierce and Ljung-Box Tests

The Cauchy Distribution

Canonical Correlations

biplot.princomp

Biplot for Principal Components

The (non-central) Chi-Squared Distribution

Pearson's Chi-squared Test for Count Data

case+variable.names

Case and Variable Names of Fitted Models

Classical (Metric) Multidimensional Scaling

Confidence Intervals for Model Parameters

Extract Model Coefficients

Linearly Constrained Optimization

Correlation, Variance and Covariance (Matrices)

Cophenetic Distances for a Hierarchical Clustering

Convolution of Sequences via FFT

Find Complete Cases

Test for Association/Correlation Between Paired Samples

(Possibly Sparse) Contrast Matrices

Get and Set Contrast Matrices

Symbolic and Algorithmic Derivatives of Simple Expressions

Kernel Density Estimation

Classical Seasonal Decomposition by Moving Averages

Cut a Tree into Groups of Data

Weighted Covariance Matrices

delete.response

Modify Terms Objects

Apply a Function to All Nodes of a Dendrogram

Residual Degrees-of-Freedom

Plot Cumulative Periodogram

Effects from Fitted Model

Fligner-Killeen Test of Homogeneity of Variances

Embedding a Time Series

Distributions in the stats package

Tukey Five-Number Summaries

Extract Model Fitted Values

Extract Coefficients in Original Coding

Empirical Cumulative Distribution Function

Compute Efficiencies of Multistratum Analysis of Variance

Formula Notation for Flat Contingency Tables

Flat Contingency Tables

Linear Filtering on a Time Series

Discrete Integration: Inverse of Differencing

Distance Matrix Computation

Extract Model Formula from nls Object

Fisher's Exact Test for Count Data

The F Distribution

Friedman Rank Sum Test

Fast Discrete Fourier Transform (FFT)

Fitting Generalized Linear Models

The Hypergeometric Distribution

Holt-Winters Filtering

Accessing Generalized Linear Model Fits

K-Means Clustering

Get Initial Parameter Estimates

Kruskal-Wallis Rank Sum Test

The Interquartile Range

Auxiliary for Controlling GLM Fitting

Test if a Model's Formula is Empty

Isotonic / Monotone Regression

Kalman Filtering

Hierarchical Clustering

Median Polish of a Matrix

Kolmogorov-Smirnov Tests

Draw a Heat Map

Accessing Linear Model Fits

Kernel Regression Smoother

Fitter Functions for Linear Models

Regression Diagnostics

Fitting Linear Models

Print lsfit Regression Results

Compute Diagnostics for lsfit Regression Results

Adjust for Missing Values

mantelhaen.test

Cochran-Mantel-Haenszel Chi-Squared Test for Count Data

Multivariate Analysis of Variance

Control the Iterations in nls

The Negative Binomial Distribution

NLSstAsymptotic

Fit the Asymptotic Regression Model

order.dendrogram

Ordering or Labels of the Leaves in a Dendrogram

Power calculations for one and two sample t tests

power.prop.test

Power Calculations for Two-Sample Test for Proportions

Adjust P-values for Multiple Comparisons

predict.HoltWinters

Prediction Function for Fitted Holt-Winters Models

Model Predictions

Time Series Lag Plots

Lag a Time Series

Print Loadings in Factor Analysis

Set Parameters for Loess

Create a Link for GLM Families

Mood Two-Sample Test of Scale

makepredictcall

Utility Function for Safe Prediction

The Multinomial Distribution

Handle Missing Values in Objects

Plot Method for Kernel Density Estimation

Plot Autocovariance and Autocorrelation Functions

Adjust for Missing Values

Plotting Spectral Densities

plot.profile.nls

Plot a profile.nls Object

expand.model.frame

Add new variables to a model frame

Compute Allowed Changes in Adding to or Dropping from a Formula

Family Objects for Models

Extract AIC from a Fitted Model

The Geometric Distribution

The Gamma Distribution

Robust Line Fitting

interaction.plot

Two-way Interaction Plot

Integration of One-Dimensional Functions

A Class for Lists of (Parts of) Model Fits

identify.hclust

Identify Clusters in a Dendrogram

Apply Smoothing Kernel

influence.measures

Regression Deletion Diagnostics

Extract Log-Likelihood

The Logistic Distribution

Local Polynomial Regression Fitting

Smoothing Kernel Objects

Mahalanobis Distance

Find the Least Squares Fit

Mauchly's Test of Sphericity

McNemar's Chi-squared Test for Count Data

Inverse Interpolation

NLSstLfAsymptote

Horizontal Asymptote on the Left Side

Plotting Time-Series Objects

Plot Step Functions

Phillips-Perron Test for Unit Roots

Fitting Log-Linear Models

Ordinates for Probability Plotting

Extract Components from a Model Frame

Construct Design Matrices

Highly Composite Numbers

Non-Linear Minimization

Compute Tables of Results from an Aov Model Fit

The Log Normal Distribution

Scatter Plot Smoothing

The Normal Distribution

Find Longest Contiguous Stretch of non-NAs

Plot a Seasonal or other Subseries from a Time Series

NLSstRtAsymptote

Horizontal Asymptote on the Right Side

Include an Offset in a Model Formula

Test for Equal Means in a One-Way Layout

Tabulate p values for pairwise comparisons

Plot Diagnostics for an lm Object

Plot Ridge Functions for Projection Pursuit Regression Fit

pairwise.wilcox.test

Pairwise Wilcoxon Rank Sum Tests

Extract the Number of Observations from a Fit.

plot.HoltWinters

Plot function for HoltWinters objects

pairwise.prop.test

Pairwise comparisons for proportions

pairwise.t.test

Pairwise t tests

Plot Method for isoreg Objects

Forecast from ARIMA fits

Predict Method for GLM Fits

Predict method for Linear Model Fits

Test of Equal or Given Proportions

Predict Loess Curve or Surface

Projection Pursuit Regression

Principal Components Analysis

Predicting from Nonlinear Least Squares Fits

predict.smooth.spline

Predict from Smoothing Spline Fit

Shapiro-Wilk Normality Test

Distribution of the Wilcoxon Signed Rank Statistic

Taper a Time Series by a Cosine Bell

Generic Function for Profiling Models

Print Coefficient Matrices

Running Medians -- Robust Scatter Plot Smoothing

Random Wishart Distributed Matrices

Scatter Plot with Smooth Curve Fitted by Loess

End Points Smoothing (for Running Medians)

Create a sortedXyData Object

Self-Starting Nls Biexponential model

SSD Matrix and Estimated Variance Matrix in Multivariate Models

prop.trend.test

Test for trend in proportions

Extract Model Residuals

Reshape Grouped Data

Tukey's (Running Median) Smoothing

Fit a Smoothing Spline

Interpolating Splines

Self-Starting Nls Asymptotic Regression Model

Self-Starting Nls First-order Compartment Model

Self-Starting Nls Four-Parameter Logistic Model

Evaluate Derivatives Numerically

The R Stats Package

General-purpose Optimization

One Dimensional Optimization

The Poisson Distribution

Create a Power Link Object

power.anova.test

Power Calculations for Balanced One-Way Analysis of Variance Tests

Exact Poisson tests

print.power.htest

Print Methods for Hypothesis Tests and Power Calculation Objects

Method for Profiling nls Objects

Printing and Formatting of Time-Series Objects

Pre-computations for a Plotting Object

Principal Components Analysis

Sample Quantiles

Random 2-way Tables with Given Marginals

reorder.default

Reorder Levels of a Factor

Standard Deviation

Number of Replications of Terms

Standard Errors for Contrasts in Model Terms

Estimate Spectral Density of a Time Series from AR Fit

Estimate Spectral Density of a Time Series by a Smoothed Periodogram

Projections of Models

Manipulate Flat Contingency Tables

Draw Rectangles Around Hierarchical Clusters

Construct Self-starting Nonlinear Models

Set the Names in an Object

Self-Starting Nls Asymptotic Regression Model with an Offset

Self-Starting Nls Asymptotic Regression Model through the Origin

Plot Regression Terms

Construct a terms Object from a Formula

Methods for STL Objects

Plot Multiple Time Series

Fit Structural Time Series

Friedman's SuperSmoother

Symbolic Number Coding

Description of Terms Objects

Update and Re-fit a Model Call

weighted.residuals

Compute Weighted Residuals

F Test to Compare Two Variances

Encode the Terminal Times of Time Series

Extract Model Weights

GLM Anova Statistics

Step Functions - Creation and Class

Seasonal Decomposition of Time Series by Loess

Student's t-Test

The Student t Distribution

Compute Tukey Honest Significant Differences

Choose a model by AIC in a Stepwise Algorithm

The Uniform Distribution

Diagnostic Plots for Time-Series Fits

Summarizing Non-Linear Least-Squares Model Fits

summary.princomp

Summary method for Principal Components Analysis

Tsp Attribute of Time-Series-like Objects

Rotation Methods for Factor Analysis

Quantile-Quantile Plots

Calculate Variance-Covariance Matrix for a Fitted Model Object

Reorder Levels of Factor

reorder.dendrogram

Reorder a Dendrogram

Self-Starting Nls Gompertz Growth Model

Summarize an Analysis of Variance Model

Self-Starting Nls Logistic Model

Summarizing Generalized Linear Model Fits

Summarizing Linear Model Fits

Summary Method for Multivariate Analysis of Variance

Sampling Times of Time Series

Form Symmetric Toeplitz Matrix

The Studentized Range Distribution

Use Fixed-Interval Smoothing on Time Series

Spectral Density Estimation

Sets Contrasts for a Factor

Self-Starting Nls Michaelis-Menten Model

Self-Starting Nls Weibull Growth Curve Model

Defunct Functions in Package stats

stats-deprecated

Deprecated Functions in Package stats

Methods for Time Series Objects

Time-Series Objects

One Dimensional Root (Zero) Finding

The Weibull Distribution

Wilcoxon Rank Sum and Signed Rank Tests

Bind Two or More Time Series

Distribution of the Wilcoxon Rank Sum Statistic

Weighted Arithmetic Mean