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stats (version 3.2.2)

The R Stats Package

Description

R statistical functions.

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Version

Version

3.2.2

License

Part of R 3.2.2

Maintainer

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

Last Published

December 12th, 2019

Functions in stats (3.2.2)

Find Aliases (Dependencies) in a Model

Compute an AR Process Exactly Fitting an ACF

Analysis of Deviance for Generalized Linear Model Fits

Auto- and Cross- Covariance and -Correlation Function Estimation

Add or Drop All Possible Single Terms to a Model

Compute Summary Statistics of Data Subsets

Akaike's An Information Criterion

ANOVA for Linear Model Fits

Puts Arbitrary Margins on Multidimensional Tables or Arrays

Fit an Analysis of Variance Model

Fit Autoregressive Models to Time Series by OLS

ARIMA Modelling of Time Series

Ansari-Bradley Test

Comparisons between Multivariate Linear Models

Fit Autoregressive Models to Time Series

ARIMA Modelling of Time Series -- Preliminary Version

Compute Theoretical ACF for an ARMA Process

Simulate from an ARIMA Model

Interpolation Functions

Convert ARMA Process to Infinite MA Process

Biplot of Multivariate Data

The Binomial Distribution

asOneSidedFormula

Convert to One-Sided Formula

Group Averages Over Level Combinations of Factors

The Beta Distribution

Convert Objects to Class hclust

Bandwidth Selectors for Kernel Density Estimation

Bartlett Test of Homogeneity of Variances

Exact Binomial Test

biplot.princomp

Biplot for Principal Components

Canonical Correlations

The (non-central) Chi-Squared Distribution

Probability of coincidences

Box-Pierce and Ljung-Box Tests

Pearson's Chi-squared Test for Count Data

.checkMFClasses

Functions to Check the Type of Variables passed to Model Frames

case+variable.names

Case and Variable Names of Fitted Models

Classical (Metric) Multidimensional Scaling

The Cauchy Distribution

Convolution of Sequences via FFT

Extract Model Coefficients

Cophenetic Distances for a Hierarchical Clustering

(Possibly Sparse) Contrast Matrices

Get and Set Contrast Matrices

Correlation, Variance and Covariance (Matrices)

Confidence Intervals for Model Parameters

Find Complete Cases

Test for Association/Correlation Between Paired Samples

Linearly Constrained Optimization

Plot Cumulative Periodogram

delete.response

Modify Terms Objects

Cut a Tree into Groups of Data

Residual Degrees-of-Freedom

Symbolic and Algorithmic Derivatives of Simple Expressions

Classical Seasonal Decomposition by Moving Averages

Kernel Density Estimation

Apply a Function to All Nodes of a Dendrogram

Weighted Covariance Matrices

Extract AIC from a Fitted Model

Empirical Cumulative Distribution Function

Distributions in the stats package

Compute Efficiencies of Multistratum Analysis of Variance

Embedding a Time Series

Effects from Fitted Model

Distance Matrix Computation

Extract Coefficients in Original Coding

expand.model.frame

Add new variables to a model frame

Discrete Integration: Inverse of Differencing

The F Distribution

Fast Discrete Fourier Transform (FFT)

Linear Filtering on a Time Series

Fisher's Exact Test for Count Data

Accessing Generalized Linear Model Fits

Fitting Generalized Linear Models

The Interquartile Range

Auxiliary for Controlling GLM Fitting

Get Initial Parameter Estimates

Test if a Model's Formula is Empty

Kolmogorov-Smirnov Tests

Kernel Regression Smoother

Create a Link for GLM Families

influence.measures

Regression Deletion Diagnostics

identify.hclust

Identify Clusters in a Dendrogram

Compute Allowed Changes in Adding to or Dropping from a Formula

Median Polish of a Matrix

makepredictcall

Utility Function for Safe Prediction

Family Objects for Models

Lag a Time Series

Friedman Rank Sum Test

Extract Model Formula from nls Object

Scatter Plot Smoothing

The Log Normal Distribution

Time Series Lag Plots

Regression Diagnostics

Fitting Linear Models

Tukey Five-Number Summaries

Extract Model Fitted Values

The Gamma Distribution

The Geometric Distribution

Hierarchical Clustering

Draw a Heat Map

Apply Smoothing Kernel

Print Loadings in Factor Analysis

Smoothing Kernel Objects

Set Parameters for Loess

The Hypergeometric Distribution

Holt-Winters Filtering

Accessing Linear Model Fits

Kalman Filtering

Isotonic / Monotone Regression

Find Longest Contiguous Stretch of non-NAs

Fitter Functions for Linear Models

NLSstLfAsymptote

Horizontal Asymptote on the Left Side

Inverse Interpolation

Fligner-Killeen Test of Homogeneity of Variances

Formula Notation for Flat Contingency Tables

Flat Contingency Tables

K-Means Clustering

interaction.plot

Two-way Interaction Plot

Integration of One-Dimensional Functions

Kruskal-Wallis Rank Sum Test

A Class for Lists of (Parts of) Model Fits

pairwise.prop.test

Pairwise comparisons for proportions

Robust Line Fitting

pairwise.t.test

Pairwise t tests

Plot Ridge Functions for Projection Pursuit Regression Fit

Plot Diagnostics for an lm Object

Printing and Formatting of Time-Series Objects

Method for Profiling nls Objects

Forecast from ARIMA fits

Projections of Models

print.power.htest

Print Methods for Hypothesis Tests and Power Calculation Objects

Predict Method for GLM Fits

Predict method for Linear Model Fits

Predict Loess Curve or Surface

Sample Quantiles

Draw Rectangles Around Hierarchical Clusters

Manipulate Flat Contingency Tables

Random 2-way Tables with Given Marginals

Self-Starting Nls Asymptotic Regression Model with an Offset

Self-Starting Nls Asymptotic Regression Model through the Origin

GLM Anova Statistics

Encode the Terminal Times of Time Series

Compute Diagnostics for lsfit Regression Results

Print lsfit Regression Results

Multivariate Analysis of Variance

mantelhaen.test

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

The Normal Distribution

Highly Composite Numbers

Non-Linear Minimization

order.dendrogram

Ordering or Labels of the Leaves in a Dendrogram

Evaluate Derivatives Numerically

Extract Log-Likelihood

Adjust P-values for Multiple Comparisons

Fitting Log-Linear Models

Mauchly's Test of Sphericity

McNemar's Chi-squared Test for Count Data

The Multinomial Distribution

Mood Two-Sample Test of Scale

Include an Offset in a Model Formula

One Dimensional Optimization

Test for Equal Means in a One-Way Layout

General-purpose Optimization

Local Polynomial Regression Fitting

The Logistic Distribution

Find the Least Squares Fit

Mahalanobis Distance

Adjust for Missing Values

Construct Design Matrices

Extract Components from a Model Frame

plot.HoltWinters

Plot function for HoltWinters objects

The Negative Binomial Distribution

Plot Method for isoreg Objects

Create a Power Link Object

predict.HoltWinters

Prediction Function for Fitted Holt-Winters Models

Set the Names in an Object

Model Predictions

Construct Self-starting Nonlinear Models

Plot Autocovariance and Autocorrelation Functions

Estimate Spectral Density of a Time Series by a Smoothed Periodogram

Extract the Number of Observations from a Fit.

Estimate Spectral Density of a Time Series from AR Fit

power.prop.test

Power Calculations for Two-Sample Test for Proportions

plot.profile.nls

Plot a profile.nls Object

Plot Method for Kernel Density Estimation

Power calculations for one and two sample t tests

Compute Tables of Results from an Aov Model Fit

prop.trend.test

Test for trend in proportions

Plot a Seasonal or other Subseries from a Time Series

Handle Missing Values in Objects

Control the Iterations in nls

Adjust for Missing Values

NLSstAsymptotic

Fit the Asymptotic Regression Model

pairwise.wilcox.test

Pairwise Wilcoxon Rank Sum Tests

Tabulate p values for pairwise comparisons

The Poisson Distribution

Exact Poisson tests

NLSstRtAsymptote

Horizontal Asymptote on the Right Side

Defunct Functions in Package stats

stats-deprecated

Deprecated Functions in Package stats

Self-Starting Nls Gompertz Growth Model

The Student t Distribution

Student's t-Test

Methods for Time Series Objects

Time-Series Objects

Plotting Spectral Densities

F Test to Compare Two Variances

power.anova.test

Power Calculations for Balanced One-Way Analysis of Variance Tests

Update and Re-fit a Model Call

Random Wishart Distributed Matrices

Running Medians -- Robust Scatter Plot Smoothing

Self-Starting Nls First-order Compartment Model

End Points Smoothing (for Running Medians)

Create a sortedXyData Object

Standard Deviation

Symbolic Number Coding

Description of Terms Objects

Test of Equal or Given Proportions

Friedman's SuperSmoother

The Studentized Range Distribution

Use Fixed-Interval Smoothing on Time Series

Plot Step Functions

Phillips-Perron Test for Unit Roots

Plotting Time-Series Objects

Ordinates for Probability Plotting

Generic Function for Profiling Models

Print Coefficient Matrices

Pre-computations for a Plotting Object

Principal Components Analysis

Reshape Grouped Data

Extract Model Residuals

Projection Pursuit Regression

Principal Components Analysis

predict.smooth.spline

Predict from Smoothing Spline Fit

Quantile-Quantile Plots

Standard Errors for Contrasts in Model Terms

reorder.default

Reorder Levels of a Factor

Tukey's (Running Median) Smoothing

Fit a Smoothing Spline

Number of Replications of Terms

reorder.dendrogram

Reorder a Dendrogram

Reorder Levels of Factor

Shapiro-Wilk Normality Test

Distribution of the Wilcoxon Signed Rank Statistic

Self-Starting Nls Michaelis-Menten Model

Self-Starting Nls Weibull Growth Curve Model

Step Functions - Creation and Class

Summarizing Linear Model Fits

Scatter Plot with Smooth Curve Fitted by Loess

Seasonal Decomposition of Time Series by Loess

Self-Starting Nls Four-Parameter Logistic Model

Taper a Time Series by a Cosine Bell

Spectral Density Estimation

The R Stats Package

Choose a model by AIC in a Stepwise Algorithm

Form Symmetric Toeplitz Matrix

Sampling Times of Time Series

The Uniform Distribution

Compute Tukey Honest Significant Differences

Self-Starting Nls Logistic Model

weighted.residuals

Compute Weighted Residuals

Predicting from Nonlinear Least Squares Fits

Self-Starting Nls Biexponential model

Extract Model Weights

SSD Matrix and Estimated Variance Matrix in Multivariate Models

Self-Starting Nls Asymptotic Regression Model

Interpolating Splines

Summarize an Analysis of Variance Model

Summarizing Generalized Linear Model Fits

summary.princomp

Summary method for Principal Components Analysis

Summarizing Non-Linear Least-Squares Model Fits

Diagnostic Plots for Time-Series Fits

Summary Method for Multivariate Analysis of Variance

Plot Multiple Time Series

Wilcoxon Rank Sum and Signed Rank Tests

Bind Two or More Time Series

Methods for STL Objects

Distribution of the Wilcoxon Rank Sum Statistic

Plot Regression Terms

Fit Structural Time Series

Construct a terms Object from a Formula

Rotation Methods for Factor Analysis

Weighted Arithmetic Mean

The Weibull Distribution

Calculate Variance-Covariance Matrix for a Fitted Model Object

Tsp Attribute of Time-Series-like Objects

One Dimensional Root (Zero) Finding

Sets Contrasts for a Factor