Description Usage Arguments Details Value Author References Examples
View source: R/detectEWMAMeanCDR.R
Given a vector x
, use the EWMA method to sequentially detect changes
(or a single change) in the MEAN of the vector.
1 2 3 
x 
The vector (stream) in which to detect change(s). 
r 
Control parameter for EWMA. Must be in range [0,1].
Default is 
L 
Control parameter for EWMA. Default is 
BL 
The burnin length. Default is 
multiple 
Boolean to use to decide whether to detect multiple changes
or only a single change. Default is 
single 
Boolean to use to decide whether to detect only a single
change or multiple changes. Set to 
usePrechange 
Boolean indicating whether prechange parameters
(mean and variance) are known and will be used
(or not). Default is

prechangeMean 
Value to be used for the prechange mean.
Default is 
prechangeSigma 
Value to be used for the prechange standard
deviation. Default is 
prechangeVar 
Value to be used for the prechange variance.
Default is 
skipCheck 
A boolean which allows the function to skip the check
of the stream. Default is 
EWMA updates via:
Z_{j} = (1r) Z_{j1} + r x_{j}
where μ is the mean of the incontrol stream, x_j is the observation at time j and r is a control parameter for EWMA. Then, a change is signalled if
Z_j  μ > L σ_{Z_j}
, where L is the other control parameter, and σ_{Z_j} is a scaled version of the incontrol variance σ. This is the formulation for using EWMA to detect an increase or decrease in the mean.
A list with the following elements:
tauhat
A vector of the changepoints found.
Dean Bodenham
S. W. Roberts (1959) Control chart tests based on geometric moving averages. Technometrics, 1(3), 239250
1 2 3 4 5 6 7 8 9 10 11 12 13 14  # create a stream with three changepoints
set.seed(8)
x < rnorm(400, 5, 1) + rep(c(0:3), each=100) # mean is 5 and s.d. is 1
# multiple changepoints
list_ewma < detectEWMAMean(x, r=0.25, L=3.023, BL=50, multiple=TRUE)
# now only a single (the first) changepoint
list_ewma2 < detectEWMAMean(x, r=0.25, L=3.023, BL=50, single=TRUE)
# now only a single (the first) changepoint, but with the prechange
# mean and variance known
list_ewma3 < detectEWMAMean(x, r=0.25, L=3.023, BL=50, single=TRUE,
prechangeMean=5, prechangeSigma=1)

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