distfreeest: Estimating Various Quantities for Distribution-Free Tolerance...
In tolerance: Statistical Tolerance Intervals and Regions

Description Usage Arguments Value References See Also Examples

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

1	distfree.est(n = NULL, alpha = NULL, P = NULL, side = 1)

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

When providing two of the three quantities n, alpha, and P, distfree.est returns the third quantity. If more than one value of a certain quantity is specified, then a table will be returned.

Natrella, M. G. (1963), Experimental Statistics: National Bureau of Standards - Handbook No. 91, United States Government Printing Office, Washington, D.C.

nptol.int

 
## Solving for 1 minus the confidence level.

distfree.est(n = 59, P = 0.95, side = 1)

## Solving for the sample size.

distfree.est(alpha = 0.05, P = 0.95, side = 1)

## Solving for the proportion of the population to cover.

distfree.est(n = 59, alpha = 0.05, side = 1)

## Solving for sample sizes for many tolerance specifications.

distfree.est(alpha = seq(0.01, 0.05, 0.01), 
             P = seq(0.80, 0.99, 0.01), side = 2)