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stats (version 3.4.1)

The R Stats Package

Description

R statistical functions.

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Version

Version

3.4.1

License

Part of R 3.4.1

Maintainer

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

Last Published

December 12th, 2019

Functions in stats (3.4.1)

Convert ARMA Process to Infinite MA Process

The Beta Distribution

Akaike's An Information Criterion

Compute Theoretical ACF for an ARMA Process

The Exponential Distribution

The F Distribution

The Binomial Distribution

The Cauchy Distribution

The (non-central) Chi-Squared Distribution

Distributions in the stats package

Holt-Winters Filtering

The Hypergeometric Distribution

The Logistic Distribution

The Log Normal Distribution

Self-Starting Nls Asymptotic Regression Model with an Offset

The Gamma Distribution

The Geometric Distribution

Inverse Interpolation

NLSstLfAsymptote

Horizontal Asymptote on the Left Side

The Multinomial Distribution

NLSstAsymptotic

Fit the Asymptotic Regression Model

SSD Matrix and Estimated Variance Matrix in Multivariate Models

Self-Starting Nls Asymptotic Regression Model

Self-Starting Nls Asymptotic Regression Model through the Origin

Fit Structural Time Series

The Student t Distribution

Puts Arbitrary Margins on Multidimensional Tables or Arrays

The Interquartile Range

NLSstRtAsymptote

Horizontal Asymptote on the Right Side

The Negative Binomial Distribution

The Normal Distribution

The Poisson Distribution

Self-Starting Nls Four-Parameter Logistic Model

Self-Starting Nls Gompertz Growth Model

Kalman Filtering

Self-Starting Nls Biexponential model

Self-Starting Nls First-order Compartment Model

Compute an AR Process Exactly Fitting an ACF

Add or Drop All Possible Single Terms to a Model

Self-Starting Nls Logistic Model

Self-Starting Nls Michaelis-Menten Model

Distribution of the Wilcoxon Rank Sum Statistic

Auto- and Cross- Covariance and -Correlation Function Estimation

The Studentized Range Distribution

Compute Tukey Honest Significant Differences

Fit Autoregressive Models to Time Series

Fit Autoregressive Models to Time Series by OLS

Comparisons between Multivariate Linear Models

Ansari-Bradley Test

asOneSidedFormula

Convert to One-Sided Formula

Group Averages Over Level Combinations of Factors

Compute Summary Statistics of Data Subsets

Find Aliases (Dependencies) in a Model

Self-Starting Nls Weibull Growth Curve Model

Distribution of the Wilcoxon Signed Rank Statistic

The Uniform Distribution

The Weibull Distribution

Bandwidth Selectors for Kernel Density Estimation

Bartlett Test of Homogeneity of Variances

biplot.princomp

Biplot for Principal Components

Probability of coincidences

Analysis of Deviance for Generalized Linear Model Fits

ANOVA for Linear Model Fits

ARIMA Modelling of Time Series -- Preliminary Version

Exact Binomial Test

Biplot of Multivariate Data

case+variable.names

Case and Variable Names of Fitted Models

Fit an Analysis of Variance Model

Interpolation Functions

ARIMA Modelling of Time Series

Simulate from an ARIMA Model

Extract Model Coefficients

Find Complete Cases

Weighted Covariance Matrices

Plot Cumulative Periodogram

Pearson's Chi-squared Test for Count Data

Classical (Metric) Multidimensional Scaling

Confidence Intervals for Model Parameters

Linearly Constrained Optimization

General Tree Structures

Kernel Density Estimation

Effects from Fitted Model

Embedding a Time Series

Fligner-Killeen Test of Homogeneity of Variances

Hierarchical Clustering

Symbolic and Algorithmic Derivatives of Simple Expressions

expand.model.frame

Add new variables to a model frame

Extract AIC from a Fitted Model

(Possibly Sparse) Contrast Matrices

Get and Set Contrast Matrices

Cut a Tree into Groups of Data

Classical Seasonal Decomposition by Moving Averages

Convert Objects to Class hclust

Box-Pierce and Ljung-Box Tests

Canonical Correlations

Correlation, Variance and Covariance (Matrices)

.checkMFClasses

Functions to Check the Type of Variables passed to Model Frames

Convolution of Sequences via FFT

Cophenetic Distances for a Hierarchical Clustering

Residual Degrees-of-Freedom

Family Objects for Models

Fast Discrete Fourier Transform (FFT)

Auxiliary for Controlling GLM Fitting

Accessing Generalized Linear Model Fits

Draw a Heat Map

Kolmogorov-Smirnov Tests

Kernel Regression Smoother

Robust Line Fitting

Distance Matrix Computation

Extract Coefficients in Original Coding

Extract Model Fitted Values

Test if a Model's Formula is Empty

Isotonic / Monotone Regression

Lag a Time Series

Time Series Lag Plots

Discrete Integration: Inverse of Differencing

Factor Analysis

Compute Allowed Changes in Adding to or Dropping from a Formula

Extract Model Formula from nls Object

Friedman Rank Sum Test

identify.hclust

Identify Clusters in a Dendrogram

influence.measures

Regression Deletion Diagnostics

Apply Smoothing Kernel

Smoothing Kernel Objects

Fitting Linear Models

Mahalanobis Distance

Create a Link for GLM Families

McNemar's Chi-squared Test for Count Data

A Class for Lists of (Parts of) Model Fits

Set Parameters for Loess

Extract Log-Likelihood

mantelhaen.test

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

Regression Diagnostics

Test for Association/Correlation Between Paired Samples

delete.response

Modify Terms Objects

Apply a Function to All Nodes of a Dendrogram

Empirical Cumulative Distribution Function

Compute Efficiencies of Multistratum Analysis of Variance

Linear Filtering on a Time Series

Fisher's Exact Test for Count Data

Flat Contingency Tables

Tukey Five-Number Summaries

Get Initial Parameter Estimates

Fitting Generalized Linear Models

Integration of One-Dimensional Functions

Compute Diagnostics for lsfit Regression Results

Print lsfit Regression Results

Median Polish (Robust Twoway Decomposition) of a Matrix

Extract Components from a Model Frame

Mauchly's Test of Sphericity

Adjust for Missing Values

Adjust for Missing Values

Test for Equal Means in a One-Way Layout

Compute Tables of Results from an Aov Model Fit

Plot a Seasonal or other Subseries from a Time Series

Optimization using PORT routines

Nonlinear Least Squares

General-purpose Optimization

pairwise.t.test

Pairwise t tests

Tabulate p values for pairwise comparisons

Plotting Time-Series Objects

Find Longest Contiguous Stretch of non-NAs

Handle Missing Values in Objects

Control the Iterations in nls

pairwise.wilcox.test

Pairwise Wilcoxon Rank Sum Tests

plot.HoltWinters

Plot function for HoltWinters objects

Plotting Spectral Densities

Plot Step Functions

interaction.plot

Two-way Interaction Plot

Accessing Linear Model Fits

Fitter Functions for Linear Models

Fitting Log-Linear Models

Exact Poisson tests

Principal Components Analysis

predict.HoltWinters

Prediction Function for Fitted Holt-Winters Models

Principal Components Analysis

print.power.htest

Print Methods for Hypothesis Tests and Power Calculation Objects

Sample Quantiles

Formula Notation for Flat Contingency Tables

K-Means Clustering

Kruskal-Wallis Rank Sum Test

Print Loadings in Factor Analysis

Ordinates for Probability Plotting

Projection Pursuit Regression

Generic Function for Profiling Models

Method for Profiling nls Objects

prop.trend.test

Test for trend in proportions

Quantile-Quantile Plots

Reshape Grouped Data

Extract Model Residuals

Tukey's (Running Median) Smoothing

Fit a Smoothing Spline

stats-deprecated

Deprecated Functions in Package stats

Standard Deviation

Standard Errors for Contrasts in Model Terms

Extract the Number of Observations from a Fit.

Plot Method for isoreg Objects

Plot Diagnostics for an lm Object

power.anova.test

Power Calculations for Balanced One-Way Analysis of Variance Tests

Local Polynomial Regression Fitting

Find the Least Squares Fit

Median Absolute Deviation

makepredictcall

Utility Function for Safe Prediction

Multivariate Analysis of Variance

Mood Two-Sample Test of Scale

Evaluate Derivatives Numerically

Construct Self-starting Nonlinear Models

GLM Anova Statistics

Defunct Functions in Package stats

Summarizing Non-Linear Least-Squares Model Fits

summary.princomp

Summary method for Principal Components Analysis

Student's t-Test

Plot Regression Terms

Diagnostic Plots for Time-Series Fits

Tsp Attribute of Time-Series-like Objects

Extract Model Weights

Wilcoxon Rank Sum and Signed Rank Tests

Include an Offset in a Model Formula

Plot Autocovariance and Autocorrelation Functions

Plot Method for Kernel Density Estimation

Scatter Plot Smoothing

Extracting the Model Frame from a Formula or Fit

Construct Design Matrices

Highly Composite Numbers

power.prop.test

Power Calculations for Two-Sample Test for Proportions

Predict Method for GLM Fits

Predict method for Linear Model Fits

predict.smooth.spline

Predict from Smoothing Spline Fit

Plot Ridge Functions for Projection Pursuit Regression Fit

The R Stats Package

Choose a model by AIC in a Stepwise Algorithm

Step Functions - Creation and Class

Pre-computations for a Plotting Object

Manipulate Flat Contingency Tables

Draw Rectangles Around Hierarchical Clusters

reorder.default

Reorder Levels of a Factor

Non-Linear Minimization

One Dimensional Optimization

order.dendrogram

Ordering or Labels of the Leaves in a Dendrogram

plot.profile.nls

Plot a profile.nls Object

Power calculations for one and two sample t tests

Phillips-Perron Test for Unit Roots

Printing and Formatting of Time-Series Objects

Print Coefficient Matrices

Projections of Models

Test of Equal or Given Proportions

Running Medians -- Robust Scatter Plot Smoothing

Scatter Plot with Smooth Curve Fitted by Loess

End Points Smoothing (for Running Medians)

Create a sortedXyData Object

Estimate Spectral Density of a Time Series from AR Fit

Number of Replications of Terms

Extract Residual Standard Deviation 'Sigma'

Simulate Responses

Adjust P-values for Multiple Comparisons

pairwise.prop.test

Pairwise comparisons for proportions

Compute Orthogonal Polynomials

Create a Power Link Object

Friedman's SuperSmoother

Symbolic Number Coding

Time-Series Objects

Plot Multiple Time Series

Estimate Spectral Density of a Time Series by a Smoothed Periodogram

Seasonal Decomposition of Time Series by Loess

Methods for STL Objects

Form Symmetric Toeplitz Matrix

Interpolating Splines

Encode the Terminal Times of Time Series

Summarize an Analysis of Variance Model

Model Predictions

Forecast from ARIMA fits

Predict Loess Curve or Surface

Predicting from Nonlinear Least Squares Fits

Summarizing Generalized Linear Model Fits

Description of Terms Objects

Sampling Times of Time Series

Rotation Methods for Factor Analysis

Calculate Variance-Covariance Matrix for a Fitted Model Object

Methods for Time Series Objects

Bind Two or More Time Series

Use Fixed-Interval Smoothing on Time Series

F Test to Compare Two Variances

Sets Contrasts for a Factor

Cross Tabulation

Random 2-way Tables with Given Marginals

Reorder Levels of Factor

reorder.dendrogram

Reorder a Dendrogram

Random Wishart Distributed Matrices

Set the Names in an Object

Shapiro-Wilk Normality Test

Taper a Time Series by a Cosine Bell

Spectral Density Estimation

Summarizing Linear Model Fits

Summary Method for Multivariate Analysis of Variance

Construct a terms Object from a Formula

One Dimensional Root (Zero) Finding

Update and Re-fit a Model Call

Weighted Arithmetic Mean

weighted.residuals

Compute Weighted Residuals