EWMA smoothing function
Compute Exponential Weighted Moving Average.
ewmaSmooth(x, y, lambda = 0.2, start, ...)
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). |
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 = λ y_t + (1-λ) z_{t-1}
where 0 <= lambda <= 1 is the parameter which controls the weights applied.
Returns a list with elements:
x |
ordered x-values |
y |
smoothed y-values |
lambda |
the smoothing parameter |
start |
the starting value |
Luca Scrucca
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.
x <- 1:50 y <- rnorm(50, sin(x/5), 0.5) plot(x,y) lines(ewmaSmooth(x,y,lambda=0.1), col="red")
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.