OCvar-class | R Documentation |
The family "OCvar"
("Operating Characteristic"
function) of classes provides methods for creating, plotting, printing
and assessing single acceptance sampling plans for variables,
based on the Normal ("OCnormal"
) distribution.
The "OCvar"
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("OCnormal", ...)
, for example, or preferably
using the creator function OCvar
.
n
:Object of class "numeric"
. A vector of
length 1 giving the sample size.
k
:Object of class "numeric"
. 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
:Object of class "character"
. The possible
types relate to the distribution on which the plans are based on.
Currently the only supported distribution is normal
.
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 "OCnormal"
this relates to the proportion of
defectives created by the process.
s
:Object of class "numeric"
. A vector of
length 1 giving the population/sample standard deviation.
s.type
:Object of class "character"
. Only for class
"OCnormal"
, indicates whether the plan is based on the
population (s.type="known"
) or sample standard deviation
(s.type="known"
).
paccept
:Object of class "numeric"
. A numeric
vector with the probability of acceptance which correspond to the
quality as given by pd
.
signature(x="OCnormal", y="missing")
,
signature(x="numeric", y="OCnormal")
: Plot the OC curve.
signature("OCvar")
:
Show the details of the sampling plan.
signature("OCcar")
: 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.
signature(object="OCvar")
: Assess whether the
sampling plan can meet the specified Producer Risk Point
(PRP) and/or Consumer Risk Point (CRP). For details see
assess,OCvar-method
Andreas Kiermeier
Guenther, W. C. (1977) Sampling Inspection in statistical quality control, Charles Griffin and Company Limited
Hald, A. (1981), Statistical theory of sampling inspection by attributes, Academic Press.
Schilling, E. G. (1982), Acceptance Sampling in Quality Control, Dekker
OCvar
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