distfree.est

When providing two of the three quantities <code>n</code>, <code>alpha</code>, and <code>P</code>, this function solves for the 
 third quantity in the context of distribution-free tolerance intervals.

file

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.

Derek S. Young

tolerance

Statistical Tolerance Intervals and Regions

Kedai Cheng

distfree.est function

<dl> <dt>n</dt>
<dd>The necessary sample size to cover a proportion <code>P</code> of the population with
 confidence <code>1-alpha</code>. Can be a vector.</dd> <dt>alpha</dt>
<dd>1 minus the confidence level attained when it is desired to cover a proportion <code>P</code>
 of the population and a sample size <code>n</code> is provided. Can be a vector.</dd> <dt>P</dt>
<dd>The proportion of the population to be covered with confidence <code>1-alpha</code> when a sample size <code>n</code>
 is provided. Can be a vector.</dd> <dt>side</dt>
<dd>Whether a 1-sided or 2-sided tolerance interval is assumed (determined by <code>side = 1</code> or <code>side = 2</code>,
 respectively).</dd>
</dl>

Arguments

Estimating Various Quantities for Distribution-Free Tolerance Intervals — distfree.est

<dl>

 <dt>n</dt>
<dd>The necessary sample size to cover a proportion <code>P</code> of the population with
 confidence <code>1-alpha</code>. Can be a vector.</dd>

 <dt>alpha</dt>
<dd>1 minus the confidence level attained when it is desired to cover a proportion <code>P</code>
 of the population and a sample size <code>n</code> is provided. Can be a vector.</dd>

 <dt>P</dt>
<dd>The proportion of the population to be covered with confidence <code>1-alpha</code> when a sample size <code>n</code>
 is provided. Can be a vector.</dd>

 <dt>side</dt>
<dd>Whether a 1-sided or 2-sided tolerance interval is assumed (determined by <code>side = 1</code> or <code>side = 2</code>,
 respectively).</dd>


</dl>

distfree.est: Estimating Various Quantities for Distribution-Free Tolerance Intervals

Description

Usage

Value

Arguments

References

See Also

Examples