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Description

Statistical Tolerance Intervals and Regions.

Statistical tolerance limits provide the limits between which we can expect to find a specified proportion of a sampled population with a given level of confidence. This package provides functions for estimating tolerance limits (intervals) for various univariate distributions (binomial, Cauchy, discrete Pareto, exponential, two-parameter exponential, extreme value, hypergeometric, Laplace, logistic, negative binomial, negative hypergeometric, normal, Pareto, Poisson-Lindley, Poisson, uniform, and Zipf-Mandelbrot), Bayesian normal tolerance limits, multivariate normal tolerance regions, nonparametric tolerance intervals, tolerance bands for regression settings (linear regression, nonlinear regression, nonparametric regression, and multivariate regression), and analysis of variance tolerance intervals. Visualizations are also available for most of these settings.

tolerance: Statistical Tolerance Intervals and Regions

Lifecycle: stable CRAN/METACRAN CRAN status Dependencies GitHub last commit Downloads JSS RJ Handbook of Statistics

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.

We are here for a love of coding and a passion for cultivating knowledge. Let us enjoy this collaboration together!

Metadata

Version

3.0.0

License

Unknown

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