qcs.cpn {qcr} | R Documentation |
Process capability indices (Nonparametric)
Description
Calculates CNp
, CNpm
using the formulation described by Tong and Chen (1998).
Usage
qcs.cpn(
object,
parameters = c(u = 0, v = 0),
limits = c(lsl = -3, usl = 3),
q = c(lq = -3, uq = 3),
target = NULL,
median = 0,
nsigmas = 3,
confidence = 0.9973
)
Arguments
object |
qcs object of type |
parameters |
A vector specifying the |
limits |
A vector specifying the lower and upper specification limits. |
q |
A vector specifying the lower and upper quantiles. These values are necessary, if |
target |
A value specifying the target of the process.
If is |
median |
A value specifying the median of data. |
nsigmas |
A numeric value specifying the number of sigmas to use. |
confidence |
A numeric value between 0 and 1 specifying the probabilities for computing the quantiles. This values is used only when object values is provided. The default value is 0.9973. |
References
Montgomery, D.C. (1991) Introduction to Statistical Quality Control, 2nd
ed, New York, John Wiley & Sons.
Tong, L.I. and Chen, J.P. (1998), Lower confidence limits of process capability
indices for nonnormal process distributions. International Journal of Quality & Reliability Management,
Vol. 15 No. 8/9, pp. 907-19.
Examples
library(qcr)
##' data(pistonrings)
xbar <- qcs.xbar(pistonrings[1:125,],plot = TRUE)
x<-xbar$statistics[[1]]
LSL=73.99; USL=74.01
median <-median(x)
lq=as.numeric(quantile(x,probs=0.00135))
uq=as.numeric(quantile(x,probs=0.99865))
qcs.cpn(parameters = c(0,0),limits = c(LSL,USL),
median = median, q=c(lq,uq))
qcs.cpn(object = xbar,parameters = c(0,0), limits = c(LSL,USL))
qcs.cpn(object = xbar,parameters = c(1,0), limits = c(LSL,USL))
qcs.cpn(object = xbar,parameters = c(0,1), limits = c(LSL,USL))
qcs.cpn(object = xbar,parameters = c(1,1), limits = c(LSL,USL))