| ewma.qcc {qcc} | R Documentation |
Draw an EWMA chart from an object of class `qcc'.
## S3 method for class 'qcc':
ewma(object, lambda=0.2, nsigmas=object$nsigmas,
add.stats = TRUE, xlab, ylab, ylim = NULL, axes.las = 0,
restore.par = TRUE, ...)
object |
an object of class `qcc'. |
lambda |
the smoothing parameter 0 <= lambda <= 1 |
nsigmas |
a numeric value specifying th number of sigmas to use for computing control limits. |
add.stats |
a logical value indicating whether statistics and other information should be printed at the bottom of the chart. |
xlab |
a string giving the label for the x-axis. |
ylab |
a string giving the label for the y-axis. |
ylim |
a numeric vector specifying the limits for the y-axis. |
axes.las |
numeric in {0,1,2,3} specifying the style of axis labels. See help(par). |
restore.par |
a logical value indicating whether the previous par settings must be restored. If you need to add points, lines, etc. to a control chart set this to FALSE. |
... |
EWMA chart smooths a series of data based on a moving average with weights which decay exponentially. Useful to detect small and permanent variation on the mean of the process.
Returns an object of class `ewma' which inherits from the `qcc' object. No methods are specifically defined for the `ewma' class.
Luca Scrucca luca@stat.unipg.it
Montgomery, D.C. (2000) Introduction to Statistical Quality Control, 4th ed. New York: John Wiley & Sons.
Wetherill, G.B. and Brown, D.W. (1991) Statistical Process Control. New York: Chapman & Hall.
data(pistonrings) attach(pistonrings) diameter <- qcc.groups(diameter, sample) q <- qcc(diameter[1:25,], type="xbar", nsigmas=3, plot=FALSE) ewma(q, lambda=0.2) q <- qcc(diameter[1:25,], newdata=diameter[26:40,], type="xbar", plot=FALSE) ewma(q, lambda=0.2, nsigmas=2.7)