Description Objects from the Class Slots Methods Author(s) References See Also

The family `"OC2c"`

("Operating Characteristic"
function) of classes provides methods for creating, plotting, printing
and assessing single, double, and multiple acceptance sampling plans
based on the Binomial (`"OCbinomial"`

), Hypergeometric
(`"OChypergeom"`

), and Poisson (`"OCpoisson"`

) distributions.

The `"OC2c"`

class is a virtual
Class: No objects may be created from it.

However, objects from the derived classes can be created by calls of
the form `new("OCbinomial", ...)`

, for example, or preferably
using the creator function `OC2c`

.

`n`

:Object of class

`"numeric"`

. A vector of length k giving the sample size at each of the k stages of sampling, e.g. for double sampling k=2.`c`

:Object of class

`"numeric"`

. A vector of length k giving the**cumulative**acceptance numbers at each of the k stages of sampling.`r`

:Object of class

`"numeric"`

. A vector of length k giving the**cumulative**rejection numbers at each of the k stages of sampling.`type`

:Object of class

`"character"`

. The possible types relate to the distribution on which the plans are based on, namely,`binomial`

,`hypergeom`

, and`poisson`

`pd`

:Object of class

`"numeric"`

. A numeric vector indicating the quality for which a probability of acceptance is calculated under the specified sampling plan. Meaning differs for the different`types`

.For

`"OCbinomial"`

this relates to the proportion of defectives created by the process.For

`"OChypergeom"`

this relates to the proportion of population defectives created by the process.For

`"OCpoisson"`

this relates to the rate of defects (per item) created by the process.`N`

:Object of class

`"numeric"`

. Only for class`"OChypergeom"`

, a number giving the population (lot) size from which the sample is drawn.`paccept`

:Object of class

`"numeric"`

. A numeric vector with the probability of acceptance which correspond to the quality as given by`pd`

.

- plot
`signature(x="OCbinomial", y="missing")`

,

`signature(x="numeric", y="OCbinomial")`

,

`signature(x="OChypergeom", y="missing")`

,

`signature(x="numeric", y="OChypergeom")`

,

`signature(x="OCpoisson", y="missing")`

or

`signature(x="numeric", y="OCpoisson")`

: Plot the OC curve.

- show
`signature("OC2c")`

or`signature("OChypergeom")`

: Show the details of the sampling plan.- summary
`signature("OC2c")`

or`signature("OChypergeom")`

: Summarise the sampling plan. Optional argument`full`

(defaults to`FALSE`

) will show the details at all quality values (`pd`

) supplied when the object was created.- assess
`signature(objqect="OC2c")`

: Assess whether the sampling plan can meet the specified*Producer Risk Point (PRP)*and/or*Consumer Risk Point (CRP)*. For details see`assess,OC2c-method`

Andreas Kiermeier

Hald, A. (1981), *Statistical theory of sampling inspection by
attributes*, Academic Press.

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