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stats (version 3.6.2)

The R Stats Package

Description

R statistical functions.

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Version

Version

3.6.2

License

Part of R 3.6.2

Maintainer

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

Last Published

December 12th, 2019

Functions in stats (3.6.2)

The F Distribution

Compute Theoretical ACF for an ARMA Process

Akaike's An Information Criterion

Holt-Winters Filtering

The Hypergeometric Distribution

The Interquartile Range

Kalman Filtering

The Binomial Distribution

The Cauchy Distribution

Inverse Interpolation

NLSstLfAsymptote

Horizontal Asymptote on the Left Side

The Normal Distribution

The Poisson Distribution

The Logistic Distribution

The Log Normal Distribution

Self-Starting Nls Weibull Growth Curve Model

Distribution of the Wilcoxon Signed Rank Statistic

NLSstRtAsymptote

Horizontal Asymptote on the Right Side

The Negative Binomial Distribution

Distributions in the stats package

The (non-central) Chi-Squared Distribution

Self-Starting Nls Michaelis-Menten Model

Self-Starting Nls Logistic Model

Convert ARMA Process to Infinite MA Process

The Beta Distribution

NLSstAsymptotic

Fit the Asymptotic Regression Model

The Multinomial Distribution

Self-Starting Nls Asymptotic Regression Model

SSD Matrix and Estimated Variance Matrix in Multivariate Models

The Studentized Range Distribution

Self-Starting Nls Four-Parameter Logistic Model

Self-Starting Nls Gompertz Growth Model

Compute Tukey Honest Significant Differences

The Gamma Distribution

The Geometric Distribution

Compute Summary Statistics of Data Subsets

Puts Arbitrary Margins on Multidimensional Tables or Arrays

The Student t Distribution

Fit Structural Time Series

Self-Starting Nls Asymptotic Regression Model through the Origin

Self-Starting Nls Asymptotic Regression Model with an Offset

The Uniform Distribution

Comparisons between Multivariate Linear Models

Find Aliases (Dependencies) in a Model

Self-Starting Nls Biexponential model

Ansari-Bradley Test

The Weibull Distribution

Exact Binomial Test

Self-Starting Nls First-order Compartment Model

Pearson's Chi-squared Test for Count Data

Auto- and Cross- Covariance and -Correlation Function Estimation

Biplot of Multivariate Data

Distribution of the Wilcoxon Rank Sum Statistic

Compute an AR Process Exactly Fitting an ACF

Classical (Metric) Multidimensional Scaling

Add or Drop All Possible Single Terms to a Model

Analysis of Deviance for Generalized Linear Model Fits

Fit Autoregressive Models to Time Series by OLS

Group Averages Over Level Combinations of Factors

asOneSidedFormula

Convert to One-Sided Formula

Fit Autoregressive Models to Time Series

Box-Pierce and Ljung-Box Tests

Canonical Correlations

Bandwidth Selectors for Kernel Density Estimation

Extract Model Coefficients

Convolution of Sequences via FFT

Bartlett Test of Homogeneity of Variances

Find Complete Cases

Cophenetic Distances for a Hierarchical Clustering

Fit an Analysis of Variance Model

ARIMA Modelling of Time Series -- Preliminary Version

Interpolation Functions

case+variable.names

Case and Variable Names of Fitted Models

Simulate from an ARIMA Model

ANOVA for Linear Model Fits

.checkMFClasses

Functions to Check the Type of Variables passed to Model Frames

ARIMA Modelling of Time Series

Convert Objects to Class hclust

Weighted Covariance Matrices

Plot Cumulative Periodogram

Cut a Tree into Groups of Data

General Tree Structures

Confidence Intervals for Model Parameters

biplot.princomp

Biplot for Principal Components

Probability of coincidences

Kernel Density Estimation

Get and Set Contrast Matrices

Residual Degrees-of-Freedom

(Possibly Sparse) Contrast Matrices

Discrete Integration: Inverse of Differencing

Linearly Constrained Optimization

Classical Seasonal Decomposition by Moving Averages

Factor Analysis

Compute Allowed Changes in Adding to or Dropping from a Formula

Correlation, Variance and Covariance (Matrices)

Test for Association/Correlation Between Paired Samples

Distance Matrix Computation

Extract Coefficients in Original Coding

Tukey Five-Number Summaries

Extract Model Fitted Values

influence.measures

Regression Deletion Diagnostics

delete.response

Modify Terms Objects

K-Means Clustering

identify.hclust

Identify Clusters in a Dendrogram

Extracting the Model Frame from a Formula or Fit

Construct Design Matrices

Symbolic and Algorithmic Derivatives of Simple Expressions

Empirical Cumulative Distribution Function

Effects from Fitted Model

Embedding a Time Series

Compute Efficiencies of Multistratum Analysis of Variance

Linear Filtering on a Time Series

Fligner-Killeen Test of Homogeneity of Variances

Family Objects for Models

Fast Discrete Fourier Transform (FFT)

Apply a Function to All Nodes of a Dendrogram

Flat Contingency Tables

Fitting Generalized Linear Models

Print lsfit Regression Results

Formula Notation for Flat Contingency Tables

Kolmogorov-Smirnov Tests

Fisher's Exact Test for Count Data

Get Initial Parameter Estimates

expand.model.frame

Add new variables to a model frame

Extract AIC from a Fitted Model

Time Series Lag Plots

Apply Smoothing Kernel

Smoothing Kernel Objects

Extract Components from a Model Frame

Create a Link for GLM Families

Median Polish (Robust Twoway Decomposition) of a Matrix

Mahalanobis Distance

Find Longest Contiguous Stretch of non-NAs

Lag a Time Series

power.anova.test

Power Calculations for Balanced One-Way Analysis of Variance Tests

Extract Model Formula from nls Object

Friedman Rank Sum Test

Draw a Heat Map

Hierarchical Clustering

Median Absolute Deviation

Print Loadings in Factor Analysis

Find the Least Squares Fit

Integration of One-Dimensional Functions

Handle Missing Values in Objects

Robust Line Fitting

Isotonic / Monotone Regression

Kruskal-Wallis Rank Sum Test

Test for Equal Means in a One-Way Layout

General-purpose Optimization

Accessing Generalized Linear Model Fits

Auxiliary for Controlling GLM Fitting

Kernel Regression Smoother

Local Polynomial Regression Fitting

order.dendrogram

Ordering or Labels of the Leaves in a Dendrogram

Phillips-Perron Test for Unit Roots

interaction.plot

Two-way Interaction Plot

A Class for Lists of (Parts of) Model Fits

pairwise.prop.test

Pairwise comparisons for proportions

prop.trend.test

Test for trend in proportions

Adjust P-values for Multiple Comparisons

Pre-computations for a Plotting Object

Compute Orthogonal Polynomials

Test if a Model's Formula is Empty

Accessing Linear Model Fits

Set Parameters for Loess

Adjust for Missing Values

Evaluate Derivatives Numerically

Fitting Linear Models

Compute Diagnostics for lsfit Regression Results

Fitter Functions for Linear Models

One Dimensional Optimization

McNemar's Chi-squared Test for Count Data

Fitting Log-Linear Models

Create a Power Link Object

Forecast from ARIMA fits

Model Predictions

Scatter Plot Smoothing

predict.smooth.spline

Predict from Smoothing Spline Fit

Compute Tables of Results from an Aov Model Fit

Mauchly's Test of Sphericity

mantelhaen.test

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

Extract Log-Likelihood

Plot Autocovariance and Autocorrelation Functions

Standard Errors for Contrasts in Model Terms

Mood Two-Sample Test of Scale

Plot a Seasonal or other Subseries from a Time Series

Construct Self-starting Nonlinear Models

Regression Diagnostics

Quantile-Quantile Plots

Adjust for Missing Values

Multivariate Analysis of Variance

Include an Offset in a Model Formula

makepredictcall

Utility Function for Safe Prediction

Exact Poisson tests

End Points Smoothing (for Running Medians)

Predict Method for GLM Fits

reorder.default

Reorder Levels of a Factor

Plot Method for Kernel Density Estimation

Find Highly Composite Numbers

pairwise.wilcox.test

Pairwise Wilcoxon Rank Sum Tests

Non-Linear Minimization

Extract the Number of Observations from a Fit.

Control the Iterations in nls

Plot Method for isoreg Objects

power.prop.test

Power Calculations for Two-Sample Test for Proportions

Random Wishart Distributed Matrices

Number of Replications of Terms

Method for Profiling nls Objects

Plot Diagnostics for an lm Object

Principal Components Analysis

predict.HoltWinters

Prediction Function for Fitted Holt-Winters Models

Plotting Time-Series Objects

Tabulate p values for pairwise comparisons

Create a sortedXyData Object

Predict Loess Curve or Surface

Power calculations for one and two sample t tests

Plot Step Functions

pairwise.t.test

Pairwise t tests

Nonlinear Least Squares

Random 2-way Tables with Given Marginals

Summarizing Non-Linear Least-Squares Model Fits

Taper a Time Series by a Cosine Bell

Friedman's SuperSmoother

Spectral Density Estimation

Plotting Spectral Densities

plot.HoltWinters

Plot function for HoltWinters objects

Printing and Formatting of Time-Series Objects

Rotation Methods for Factor Analysis

Reorder Levels of Factor

Reshape Grouped Data

Principal Components Analysis

Projection Pursuit Regression

Ordinates for Probability Plotting

Summarizing Linear Model Fits

Projections of Models

Description of Terms Objects

print.power.htest

Print Methods for Hypothesis Tests and Power Calculation Objects

Fit a Smoothing Spline

Summary Method for Multivariate Analysis of Variance

Sample Quantiles

Tukey's (Running Median) Smoothing

Optimization using PORT routines

Print Coefficient Matrices

Running Medians -- Robust Scatter Plot Smoothing

Diagnostic Plots for Time-Series Fits

Extract Model Residuals

Interpolating Splines

Sampling Times of Time Series

Encode the Terminal Times of Time Series

Predicting from Nonlinear Least Squares Fits

summary.princomp

Summary method for Principal Components Analysis

plot.profile.nls

Plot a profile.nls Object

Scatter Plot with Smooth Curve Fitted by Loess

Defunct Functions in Package stats

Simulate Responses

Extract Residual Standard Deviation 'Sigma'

Test of Equal or Given Proportions

GLM Anova Statistics

Plot Ridge Functions for Projection Pursuit Regression Fit

Manipulate Flat Contingency Tables

Generic Function for Profiling Models

Predict method for Linear Model Fits

Weighted Arithmetic Mean

Tsp Attribute of Time-Series-like Objects

Student's t-Test

Bind Two or More Time Series

stats-deprecated

Deprecated Functions in Package stats

Draw Rectangles Around Hierarchical Clusters

Cross Tabulation

Symbolic Number Coding

Methods for STL Objects

Seasonal Decomposition of Time Series by Loess

Construct a terms Object from a Formula

Time-Series Objects

Sets Contrasts for a Factor

Plot Multiple Time Series

F Test to Compare Two Variances

Extract Model Weights

reorder.dendrogram

Reorder a Dendrogram

Step Functions - Creation and Class

Calculate Variance-Covariance Matrix for a Fitted Model Object

Set the Names in an Object

Form Symmetric Toeplitz Matrix

Estimate Spectral Density of a Time Series by a Smoothed Periodogram

Choose a model by AIC in a Stepwise Algorithm

Estimate Spectral Density of a Time Series from AR Fit

Summarizing Generalized Linear Model Fits

Standard Deviation

Use Fixed-Interval Smoothing on Time Series

Plot Regression Terms

Summarize an Analysis of Variance Model

Shapiro-Wilk Normality Test

The R Stats Package

Methods for Time Series Objects

Update and Re-fit a Model Call

One Dimensional Root (Zero) Finding

Wilcoxon Rank Sum and Signed Rank Tests

weighted.residuals

Compute Weighted Residuals

The Exponential Distribution