OCvar {AcceptanceSampling} R Documentation

## Operating Characteristics of an Acceptance Sampling Plan

### Description

The preferred way of creating new objects from the family of "OCvar" classes.

### Usage

OCvar(n, k, type=c("normal"), ...)

### Arguments

 n A vector of length 1 giving the sample size. k A vector of length 1 giving the absolute distance, in units of the standard deviation, between the specification limit (based on the distribution of the items) and the acceptance limit (based on the distribution of the sample mean). See Schilling (1982) page 226 for details. type The possible types relate to the distribution on which the plans are based on, namely, normal. ... Additional parameters passed to the class generating function for each type. See Details for options.

### Details

Typical usages are:

    OCvar(n, k, s)
OCvar(n, k, pd, s)
OCvar(n, k, pd, s, s.type)


The two forms use a default type of "normal". Note that for the normal distribution the value of the standard deviation must be given. It is assumed to be the population standard deviation; this can be changed by letting s.type="unknown".

The second form provides a the proportion of defectives, pd, for which the OC function should be calculated (default is pd=seq(0, 1, 0.01).

### Value

An object from the family of OCvar-class, namely of class OCnormal.

### References

Schilling, E. G. (1982), Acceptance Sampling in Quality Control, Dekker

Guenther, W. C (1977), Sampling Inspection in Statistical Quality Control, Charles Griffin and Co Ltd

OC2c-class

### Examples

## A normal sampling plan - st. dev. known
x <- OCvar(14, 1.205)
x ## print out a brief summary
plot(x) ## plot the OC curve
plot(x, xlim=c(0,0.4)) ## plot the useful part of the OC curve

## Assess whether the plan can meet desired risk points
assess(x, PRP=c(0.05, 0.95), CRP=c(0.2, 0.1))

summary(x, full=TRUE)


[Package AcceptanceSampling version 1.0-8 Index]