ewmaSmooth {qcc} | R Documentation |
EWMA smoothing function
Description
Compute Exponential Weighted Moving Average.
Usage
ewmaSmooth(x, y, lambda = 0.2, start, ...)
Arguments
x |
a vector of x-values. |
y |
a vector of y-values. |
lambda |
the smoothing parameter. |
start |
the starting value. |
... |
additional arguments (currently not used). |
Details
EWMA function smooths a series of data based on a moving average with weights which decay exponentially.
For each y_t
value the smoothed value is computed as
z_t = \lambda y_t + (1-\lambda) z_{t-1}
where 0 \le \lambda \le 1
is the parameter which controls the weights applied.
Value
Returns a list with elements:
x |
ordered x-values |
y |
smoothed y-values |
lambda |
the smoothing parameter |
start |
the starting value |
Author(s)
Luca Scrucca
References
Montgomery, D.C. (2005) Introduction to Statistical Quality Control, 5th ed. New York: John Wiley & Sons.
Wetherill, G.B. and Brown, D.W. (1991) Statistical Process Control. New York: Chapman & Hall.
See Also
Examples
x <- 1:50
y <- rnorm(50, sin(x/5), 0.5)
plot(x,y)
lines(ewmaSmooth(x,y,lambda=0.1), col="red")