| ewma {qcc} | R Documentation |
Create an object of class 'ewma.qcc' to compute and draw an Exponential Weighted Moving Average (EWMA) chart for statistical quality control.
ewma(data, sizes, center, std.dev, lambda = 0.2, nsigmas = 3,
data.name, labels, newdata, newsizes, newlabels,
plot = TRUE, ...)
## S3 method for class 'ewma.qcc':
print(x, ...)
## S3 method for class 'ewma.qcc':
summary(object, digits = getOption("digits"), ...)
## S3 method for class 'ewma.qcc':
plot(x, add.stats = TRUE, chart.all = TRUE,
label.limits = c("LCL", "UCL"), title, xlab, ylab, ylim,
axes.las = 0, digits = getOption("digits"),
restore.par = TRUE, ...)
data |
a data frame, a matrix or a vector containing observed data for the variable to chart. Each row of a data frame or a matrix, and each value of a vector, refers to a sample or ''rationale group''. |
sizes |
a value or a vector of values specifying the sample sizes associated with each group. If not provided the sample sizes are obtained counting the non-NA elements of each row of a data frame or a matrix; sample sizes are set all equal to one if data is a vector. |
center |
a value specifying the center of group statistics or target. |
std.dev |
a value or an available method specifying the within-group standard deviation(s) of the process. Several methods are available for estimating the standard deviation. See sd.xbar and sd.xbar.one for, respectively, the grouped data case and the individual observations case.
|
lambda |
the smoothing parameter 0 <= lambda <= 1 |
nsigmas |
a numeric value specifying the number of sigmas to use for computing control limits. |
data.name |
a string specifying the name of the variable which appears on the plots. If not provided is taken from the object given as data. |
labels |
a character vector of labels for each group. |
newdata |
a data frame, matrix or vector, as for the data argument, providing further data to plot but not included in the computations. |
newsizes |
a vector as for the sizes argument providing further data sizes to plot but not included in the computations. |
newlabels |
a character vector of labels for each new group defined in the argument newdata. |
plot |
logical. If TRUE an EWMA chart is plotted. |
add.stats |
a logical value indicating whether statistics and other information should be printed at the bottom of the chart. |
chart.all |
a logical value indicating whether both statistics for data and for newdata (if given) should be plotted. |
label.limits |
a character vector specifying the labels for control limits. |
title |
a string giving the label for the main title. |
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). |
digits |
the number of significant digits to use. |
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. |
object |
an object of class 'ewma.qcc'. |
x |
an object of class 'ewma.qcc'. |
... |
additional arguments to be passed to the generic function. |
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.qcc'.
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.
##
## Grouped-data
##
data(pistonrings)
attach(pistonrings)
diameter <- qcc.groups(diameter, sample)
q <- ewma(diameter[1:25,], lambda=0.2, nsigmas=3)
summary(q)
q <- ewma(diameter[1:25,], lambda=0.2, nsigmas=2.7, newdata=diameter[26:40,], plot = FALSE)
summary(q)
plot(q)
##
## Individual observations
##
x <- c(33.75, 33.05, 34, 33.81, 33.46, 34.02, 33.68, 33.27, 33.49, 33.20,
33.62, 33.00, 33.54, 33.12, 33.84) # viscosity data (Montgomery, pag. 242)
q <- ewma(x, lambda=0.2, nsigmas=2.7)
summary(q)