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tolerance: Statistical Tolerance Intervals and Regions

Synopsis

The tolerance package provides functions for estimating tolerance limits (intervals) for various univariate distributions, Bayesian normal tolerance limits, multivariate normal tolerance regions, nonparametric tolerance intervals, tolerance bands for regression settings, and analysis of variance tolerance intervals. Visualizations in the form of histograms, scatterplots, and control charts are also available for many of these settings. More details about the package are included in both the original JSS article as well as a subsequent Handbook of Statistics book chapter.

Other highlights:

  • Includes calculations for tolerance limits (intervals) for numerous continuous and discrete distributions.

  • Pointwise tolerance interval calculations for linear, nonlinear, nonparametric, and multivariate regression settings are available.

  • Functions for sample size determination in normal and nonparametric settings are available.

  • Includes a novel operating characteristic curve function regarding k-factors for tolerance intervals based on normality.

  • Novel nonparametric methods are included, such as the ability to construct multivariate hyperrectangular tolerance regions for setting reference regions.

Documentation

The JSS article and the Handbook of Statistics book chapter both provide documentation about the tolerance package. The RJ article provides an extensive overview of most of the normal-based procedures available within the tolerance package. Moreover, the help file also documents the references used for each function.

Examples

Additional examples for the tolerance package are currently being developed for a Shiny app.

Installation

Released and tested versions of tolerance are available via the CRAN network, and can be installed from within R via

install.packages("tolerance")

Support

The issue tickets at the GitHub repo are the primary bug reporting interface. As with the other web resources, previous issues can be searched as well.

Authors

Derek S. Young

License

GPL (>= 2)

Funding Acknowledgment

This package is based upon work supported by the Chan Zuckerberg Initiative, Grant Number 2020-225193.

Code of Conduct

As contributors and maintainers of this project, we pledge to respect all people who contribute through reporting issues, posting feature requests, updating documentation, submitting pull requests or patches, and other activities. Both contributors and maintainers must consistently demonstrate acceptable behavior, respectful communications, and professional conduct. Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct. Project maintainers who do not follow the Code of Conduct may be removed from the project team. Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by opening an issue or contacting one or more of the project maintainers. By contributing to this project, you agree to abide by its terms.

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Version

Install

install.packages('tolerance')

Monthly Downloads

1,231

Version

3.0.0

License

GPL (>= 2)

Maintainer

Last Published

April 17th, 2024

Functions in tolerance (3.0.0)

acc.samp

Acceptance Sampling
anovatol.int

Tolerance Intervals for ANOVA
K.factor.sim

Estimating K-factors for Simultaneous Tolerance Intervals Based on Normality
bayesnormtol.int

Bayesian Normal Tolerance Intervals
K.factor

Estimating K-factors for Tolerance Intervals Based on Normality
TwoParExponential

The 2-Parameter Exponential Distribution
dparetotol.int

Discrete Pareto Tolerance Intervals
exp2tol.int

2-Parameter Exponential Tolerance Intervals
dpareto.ll

Maximum Likelihood Estimation for the Discrete Pareto Distribution
diffnormtol.int

1-Sided Tolerance Limits for the Distribution of the Difference Between Two Independent Normal Random Variables
DiffProp

Difference Between Two Proportions Distribution
exptol.int

Exponential Tolerance Intervals
bonftol.int

Approximate 2-Sided Tolerance Intervals that Control the Tails Using Bonferroni's Inequality
cautol.int

Cauchy Tolerance Intervals
mvregtol.region

Multivariate (Multiple) Linear Regression Tolerance Regions
exttol.int

Weibull (or Extreme-Value) Tolerance Intervals
fidnegbintol.int

Fiducial-Based Tolerance Intervals for the Function of Two Negative Binomial Proportions
DiscretePareto

Discrete Pareto Distribution
fidbintol.int

Fiducial-Based Tolerance Intervals for the Function of Two Binomial Proportions
laptol.int

Laplace Tolerance Intervals
distfree.est

Estimating Various Quantities for Distribution-Free Tolerance Intervals
fidpoistol.int

Fiducial-Based Tolerance Intervals for the Function of Two Poisson Rates
logistol.int

Logistic (or Log-Logistic) Tolerance Intervals
gamtol.int

Gamma (or Log-Gamma) Tolerance Intervals
mvtol.region

Multivariate Normal Tolerance Regions
hypertol.int

Hypergeometric Tolerance Intervals
norm.ss

Sample Size Determination for Normal Tolerance Intervals
nptol.int

Nonparametric Tolerance Intervals
npbetol.int

Nonparametric Beta-Expectation Tolerance Intervals
negbintol.int

Negative Binomial Tolerance Intervals
nlregtol.int

Nonlinear Regression Tolerance Bounds, Version 2
norm.OC

Operating Characteristic (OC) Curves for K-Factors for Tolerance Intervals Based on Normality
npregtol.int

Nonparametric Regression Tolerance Bounds
normtol.int

Normal (or Log-Normal) Tolerance Intervals
neghypertol.int

Negative Hypergeometric Tolerance Intervals
npmvtol.region

Nonparametric Multivariate Hyperrectangular Tolerance Regions
plotly_normOC

Operating Characteristic (OC) Curves for K-Factors for Tolerance Intervals Based on Normality (a plotly version of norm.OC)
plotly_anovatol

Plotting Tolerance Intervals for ANOVA
plotly_controltol

Plotting Tolerance Intervals for Control Charts
plotly_regtol

Plotting Tolerance Intervals for Regressions
plotly_npmvtol

plotting Nonparametric Multivaraite Hyperrectangular Tolerance Region
plotly_histtol

Plotting Histograms and Corresponding Tolerance Intervals for Continuous Data
plotly_multitol

Plotting Tolerance Region for Multivariate Distributions
plottol

Plotting Capabilities for Tolerance Intervals
paretotol.int

Pareto (or Power Distribution) Tolerance Intervals
np.order

Sample Size Determination for Tolerance Limits Based on Order Statistics
tolerance-package

Statistical Tolerance Intervals and Regions
simnormtol.int

Simultaneous Normal (or Log-Normal) Tolerance Intervals
poislindtol.int

Poisson-Lindley Tolerance Intervals
umatol.int

Uniformly Most Accurate Upper Tolerance Limits for Certain Discrete Distributions
poistol.int

Poisson Tolerance Intervals
tolerance-internal

Internal Functions
uniftol.int

Uniform Tolerance Intervals
ZipfMandelbrot

Zipf-Mandelbrot Distributions
poislind.ll

Maximum Likelihood Estimation for the Discrete Poisson-Lindley Distribution
PoissonLindley

Discrete Poisson-Lindley Distribution
semiconttol.int

Generalized Intervals for Semicontinuous Data
regtol.int

(Multiple) Linear Regression Tolerance Bounds
zipftol.int

Zipf-Mandelbrot Tolerance Intervals
zm.ll

Maximum Likelihood Estimation for Zipf-Mandelbrot Models
bintol.int

Binomial Tolerance Intervals
NegHypergeometric

The Negative Hypergeometric Distribution
F1

Appell's F1 Hypergeometric Function
K.table

Tables of K-factors for Tolerance Intervals Based on Normality