distfreeest: Estimating Various Quantities for Distribution-Free Tolerance...

In tolerance: Statistical Tolerance Intervals and Regions

Estimating Various Quantities for Distribution-Free Tolerance Intervals

Description

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.

Usage

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

Arguments

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).

Value

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.

References

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

See Also

nptol.int

Examples

 
## 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)

tolerance documentation built on May 29, 2024, 7:38 a.m.