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stats (version 3.5.1)

The R Stats Package

Description

R statistical functions.

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Version

Version

3.5.1

License

Part of R 3.5.1

Maintainer

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

Last Published

December 12th, 2019

Functions in stats (3.5.1)

The Exponential Distribution

Akaike's An Information Criterion

The F Distribution

The Poisson Distribution

The Normal Distribution

Compute Theoretical ACF for an ARMA Process

Self-Starting Nls Biexponential model

The Studentized Range Distribution

Self-Starting Nls First-order Compartment Model

Compute Tukey Honest Significant Differences

The Logistic Distribution

The Log Normal Distribution

The Cauchy Distribution

Self-Starting Nls Asymptotic Regression Model with an Offset

The Binomial Distribution

Analysis of Deviance for Generalized Linear Model Fits

ANOVA for Linear Model Fits

Self-Starting Nls Asymptotic Regression Model through the Origin

ARIMA Modelling of Time Series

Self-Starting Nls Weibull Growth Curve Model

Convert ARMA Process to Infinite MA Process

Simulate from an ARIMA Model

Find Aliases (Dependencies) in a Model

Distribution of the Wilcoxon Signed Rank Statistic

Bandwidth Selectors for Kernel Density Estimation

Bartlett Test of Homogeneity of Variances

biplot.princomp

Biplot for Principal Components

Probability of coincidences

The Beta Distribution

(Possibly Sparse) Contrast Matrices

Extract Model Coefficients

Convolution of Sequences via FFT

Find Complete Cases

Cophenetic Distances for a Hierarchical Clustering

Holt-Winters Filtering

Get and Set Contrast Matrices

The Hypergeometric Distribution

Factor Analysis

Compute Allowed Changes in Adding to or Dropping from a Formula

Apply Smoothing Kernel

The Gamma Distribution

delete.response

Modify Terms Objects

Apply a Function to All Nodes of a Dendrogram

Fast Discrete Fourier Transform (FFT)

Family Objects for Models

Smoothing Kernel Objects

Auxiliary for Controlling GLM Fitting

Regression Diagnostics

The (non-central) Chi-Squared Distribution

Fitting Linear Models

Self-Starting Nls Four-Parameter Logistic Model

Mahalanobis Distance

Self-Starting Nls Gompertz Growth Model

Distribution of the Wilcoxon Rank Sum Statistic

Accessing Generalized Linear Model Fits

Auto- and Cross- Covariance and -Correlation Function Estimation

Create a Link for GLM Families

Median Polish (Robust Twoway Decomposition) of a Matrix

Distributions in the stats package

Extract Components from a Model Frame

Test if a Model's Formula is Empty

Isotonic / Monotone Regression

Non-Linear Minimization

The Geometric Distribution

Highly Composite Numbers

Inverse Interpolation

Lag a Time Series

pairwise.t.test

Pairwise t tests

Tabulate p values for pairwise comparisons

Plotting Time-Series Objects

NLSstLfAsymptote

Horizontal Asymptote on the Left Side

Fit Structural Time Series

Exact Poisson tests

Ordinates for Probability Plotting

Time Series Lag Plots

Fitting Log-Linear Models

The Interquartile Range

Ansari-Bradley Test

Kalman Filtering

Comparisons between Multivariate Linear Models

Projection Pursuit Regression

SSD Matrix and Estimated Variance Matrix in Multivariate Models

Printing and Formatting of Time-Series Objects

The Student t Distribution

asOneSidedFormula

Convert to One-Sided Formula

Compute an AR Process Exactly Fitting an ACF

Self-Starting Nls Asymptotic Regression Model

Group Averages Over Level Combinations of Factors

Self-Starting Nls Logistic Model

The Multinomial Distribution

Pearson's Chi-squared Test for Count Data

NLSstAsymptotic

Fit the Asymptotic Regression Model

Print Coefficient Matrices

Scatter Plot Smoothing

Add or Drop All Possible Single Terms to a Model

Self-Starting Nls Michaelis-Menten Model

prop.trend.test

Test for trend in proportions

Classical (Metric) Multidimensional Scaling

Quantile-Quantile Plots

The Negative Binomial Distribution

NLSstRtAsymptote

Horizontal Asymptote on the Right Side

Running Medians -- Robust Scatter Plot Smoothing

Test for Equal Means in a One-Way Layout

Fit an Analysis of Variance Model

Confidence Intervals for Model Parameters

Interpolation Functions

The Weibull Distribution

The Uniform Distribution

General-purpose Optimization

Linearly Constrained Optimization

Scatter Plot with Smooth Curve Fitted by Loess

Summary Method for Multivariate Analysis of Variance

Summarizing Linear Model Fits

ARIMA Modelling of Time Series -- Preliminary Version

Puts Arbitrary Margins on Multidimensional Tables or Arrays

Fit Autoregressive Models to Time Series

Plot Autocovariance and Autocorrelation Functions

Compute Summary Statistics of Data Subsets

Convert Objects to Class hclust

Plot Method for Kernel Density Estimation

Exact Binomial Test

Fit Autoregressive Models to Time Series by OLS

Biplot of Multivariate Data

Residual Degrees-of-Freedom

Friedman's SuperSmoother

Box-Pierce and Ljung-Box Tests

Discrete Integration: Inverse of Differencing

Canonical Correlations

case+variable.names

Case and Variable Names of Fitted Models

Test for Association/Correlation Between Paired Samples

Symbolic Number Coding

Symbolic and Algorithmic Derivatives of Simple Expressions

Bind Two or More Time Series

Correlation, Variance and Covariance (Matrices)

.checkMFClasses

Functions to Check the Type of Variables passed to Model Frames

power.anova.test

Power Calculations for Balanced One-Way Analysis of Variance Tests

Effects from Fitted Model

Embedding a Time Series

Linear Filtering on a Time Series

Fisher's Exact Test for Count Data

power.prop.test

Power Calculations for Two-Sample Test for Proportions

Plot Cumulative Periodogram

Predict Method for GLM Fits

Weighted Covariance Matrices

Predict method for Linear Model Fits

predict.smooth.spline

Predict from Smoothing Spline Fit

Use Fixed-Interval Smoothing on Time Series

Weighted Arithmetic Mean

Pre-computations for a Plotting Object

Empirical Cumulative Distribution Function

Projections of Models

Get Initial Parameter Estimates

weighted.residuals

Compute Weighted Residuals

Test of Equal or Given Proportions

Cut a Tree into Groups of Data

Compute Efficiencies of Multistratum Analysis of Variance

Fitting Generalized Linear Models

Extract Model Fitted Values

K-Means Clustering

Classical Seasonal Decomposition by Moving Averages

Standard Deviation

Kruskal-Wallis Rank Sum Test

General Tree Structures

Accessing Linear Model Fits

Fitter Functions for Linear Models

expand.model.frame

Add new variables to a model frame

Compute Diagnostics for lsfit Regression Results

Extract Coefficients in Original Coding

Distance Matrix Computation

Tukey Five-Number Summaries

Kernel Density Estimation

Extract Model Formula from nls Object

Flat Contingency Tables

Friedman Rank Sum Test

Formula Notation for Flat Contingency Tables

Hierarchical Clustering

Print Loadings in Factor Analysis

Extract AIC from a Fitted Model

Fligner-Killeen Test of Homogeneity of Variances

Print lsfit Regression Results

Set the Names in an Object

Local Polynomial Regression Fitting

Shapiro-Wilk Normality Test

Draw a Heat Map

Find the Least Squares Fit

identify.hclust

Identify Clusters in a Dendrogram

Median Absolute Deviation

stats-deprecated

Deprecated Functions in Package stats

The R Stats Package

McNemar's Chi-squared Test for Count Data

Description of Terms Objects

mantelhaen.test

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

Sampling Times of Time Series

influence.measures

Regression Deletion Diagnostics

Mood Two-Sample Test of Scale

Mauchly's Test of Sphericity

Kolmogorov-Smirnov Tests

Find Longest Contiguous Stretch of non-NAs

Control the Iterations in nls

Integration of One-Dimensional Functions

Handle Missing Values in Objects

Extract the Number of Observations from a Fit.

interaction.plot

Two-way Interaction Plot

Kernel Regression Smoother

Robust Line Fitting

Set Parameters for Loess

A Class for Lists of (Parts of) Model Fits

order.dendrogram

Ordering or Labels of the Leaves in a Dendrogram

One Dimensional Optimization

Extract Log-Likelihood

Plot Method for isoreg Objects

makepredictcall

Utility Function for Safe Prediction

Extracting the Model Frame from a Formula or Fit

Plot Diagnostics for an lm Object

pairwise.wilcox.test

Pairwise Wilcoxon Rank Sum Tests

Plotting Spectral Densities

Plot Step Functions

Multivariate Analysis of Variance

Random Wishart Distributed Matrices

plot.HoltWinters

Plot function for HoltWinters objects

Construct Design Matrices

Sets Contrasts for a Factor

Random 2-way Tables with Given Marginals

Reshape Grouped Data

Compute Tables of Results from an Aov Model Fit

Extract Residual Standard Deviation 'Sigma'

Extract Model Residuals

Model Predictions

Adjust for Missing Values

Adjust for Missing Values

Forecast from ARIMA fits

Evaluate Derivatives Numerically

Plot a Seasonal or other Subseries from a Time Series

Simulate Responses

GLM Anova Statistics

Generic Function for Profiling Models

Include an Offset in a Model Formula

Compute Orthogonal Polynomials

Create a Power Link Object

Method for Profiling nls Objects

Sample Quantiles

Principal Components Analysis

Reorder Levels of Factor

reorder.dendrogram

Reorder a Dendrogram

predict.HoltWinters

Prediction Function for Fitted Holt-Winters Models

Defunct Functions in Package stats

Optimization using PORT routines

Summarizing Non-Linear Least-Squares Model Fits

summary.princomp

Summary method for Principal Components Analysis

Principal Components Analysis

End Points Smoothing (for Running Medians)

print.power.htest

Print Methods for Hypothesis Tests and Power Calculation Objects

Diagnostic Plots for Time-Series Fits

Rotation Methods for Factor Analysis

Nonlinear Least Squares

Manipulate Flat Contingency Tables

Tsp Attribute of Time-Series-like Objects

Draw Rectangles Around Hierarchical Clusters

reorder.default

Reorder Levels of a Factor

Adjust P-values for Multiple Comparisons

Create a sortedXyData Object

Number of Replications of Terms

Taper a Time Series by a Cosine Bell

pairwise.prop.test

Pairwise comparisons for proportions

Tukey's (Running Median) Smoothing

Fit a Smoothing Spline

Spectral Density Estimation

Interpolating Splines

Encode the Terminal Times of Time Series

Calculate Variance-Covariance Matrix for a Fitted Model Object

plot.profile.nls

Plot a profile.nls Object

Power calculations for one and two sample t tests

Summarize an Analysis of Variance Model

Summarizing Generalized Linear Model Fits

Phillips-Perron Test for Unit Roots

Plot Ridge Functions for Projection Pursuit Regression Fit

Seasonal Decomposition of Time Series by Loess

Form Symmetric Toeplitz Matrix

Predict Loess Curve or Surface

Standard Errors for Contrasts in Model Terms

Predicting from Nonlinear Least Squares Fits

Methods for Time Series Objects

Construct Self-starting Nonlinear Models

Methods for STL Objects

Estimate Spectral Density of a Time Series from AR Fit

Extract Model Weights

F Test to Compare Two Variances

Student's t-Test

Wilcoxon Rank Sum and Signed Rank Tests

Plot Regression Terms

Estimate Spectral Density of a Time Series by a Smoothed Periodogram

Step Functions - Creation and Class

Choose a model by AIC in a Stepwise Algorithm

Time-Series Objects

Construct a terms Object from a Formula

Update and Re-fit a Model Call

One Dimensional Root (Zero) Finding

Plot Multiple Time Series

Cross Tabulation