ewmaSmooth: EWMA smoothing function

In qcc: Quality Control Charts

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 = λ y_t + (1-λ) z_{t-1}

where 0 <= lambda <= 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

qcc, cusum

Examples

x <- 1:50
y <- rnorm(50, sin(x/5), 0.5)
plot(x,y)
lines(ewmaSmooth(x,y,lambda=0.1), col="red")

Example output

Package 'qcc' version 2.7
Type 'citation("qcc")' for citing this R package in publications.

qcc documentation built on May 2, 2019, 9:15 a.m.