qcs.hat.cpm | R Documentation |
Estimate "cpm"
using the method described by Kerstin Vannman(2001).
qcs.hat.cpm( object, limits = c(lsl = -3, usl = 3), target = NULL, mu = 0, std.dev = 1, nsigmas = 3, k0 = 1, alpha = 0.05, n = 50, contour = TRUE, ylim = NULL, ... )
object |
qcs object of type |
limits |
A vector specifying the lower and upper specification limits. |
target |
A value specifying the target of the process.
If is |
mu |
A value specifying the mean of data. |
std.dev |
A value specifying the within-group standard deviation. |
nsigmas |
A numeric value specifying the number of sigmas to use. |
k0 |
A numeric value. If the capacity index exceeds the |
alpha |
The significance level (0.05 for default) |
n |
Size of the sample. |
contour |
Logical value indicating whether contour graph should be plotted. |
ylim |
The y limits of the plot. |
... |
Arguments to be passed to or from methods. |
Montgomery, D.C. (1991) Introduction to Statistical Quality Control, 2nd
ed, New York, John Wiley & Sons.
Vannman, K. (2001). A Graphical Method to Control Process Capability. Frontiers in Statistical Quality Control,
No 6, Editors: H-J Lenz and P-TH Wilrich. Physica-Verlag, Heidelberg, 290-311.
Hubele and Vannman (2004). The E???ect of Pooled and Un-pooled Variance Estimators on Cpm When Using Subsamples.
Journal Quality Technology, 36, 207-222.
library(qcr) data(pistonrings) xbar <- qcs.xbar(pistonrings[1:125,],plot = TRUE) mu <-xbar$center std.dev <-xbar$std.dev LSL=73.99; USL=74.01 qcs.hat.cpm(limits = c(LSL,USL), mu = mu,std.dev = std.dev,ylim=c(0,1)) qcs.hat.cpm(object = xbar, limits = c(LSL,USL),ylim=c(0,1))
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