tolerance: 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.

Version: 2.0.0
Depends: R (≥ 3.5.0)
Imports: MASS, rgl, stats4
Published: 2020-02-05
Author: Derek S. Young [aut, cre]
Maintainer: Derek S. Young <derek.young at uky.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: tolerance citation info
Materials: NEWS
In views: Distributions
CRAN checks: tolerance results

Documentation:

Reference manual: tolerance.pdf

Downloads:

Package source: tolerance_2.0.0.tar.gz
Windows binaries: r-devel: tolerance_2.0.0.zip, r-release: tolerance_2.0.0.zip, r-oldrel: tolerance_2.0.0.zip
macOS binaries: r-release (arm64): tolerance_2.0.0.tgz, r-oldrel (arm64): tolerance_2.0.0.tgz, r-release (x86_64): tolerance_2.0.0.tgz
Old sources: tolerance archive

Reverse dependencies:

Reverse imports: adamethods, fdasrvf, imprecise101, zipfextR
Reverse suggests: PredictionR

Linking:

Please use the canonical form https://CRAN.R-project.org/package=tolerance to link to this page.