Description Usage Arguments Details Value Methods (by class) References Examples
Test on deviceevents using the EWMA method based on the normal distribution.
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df 
Required input data frame of class

... 
Further arguments passed onto 
ts_event 
Required if Default: Example: 
analysis_of 
Optional string indicating the English description of what
was analyzed. If specified, this will override the name of the
Default: Example: 
eval_period 
Optional positive integer indicating the number of unique times counting in reverse chronological order to assess. This will be used to establish the process mean and moving range. Default: 
delta 
Required number of sigmas at which to detect a mean shift. Sigma in this context refers to the estimated standard deviation of the EWMA statistic. Default: 
lambda 
Required "memory" parameter in the range (0, 1]. Lower values assign more weight to prior measurements. A value of 1 indicates no memory and only considers the current measurement. Default: 
zero_rate 
Required maximum proportion of Default: 
mu 
Optional value of the incontrol process mean, typically measured from historical data. Default: 
sigma 
Optional value of the incontrol process standard deviation, typically measured from historical data. Default: 
Function ewma()
is an implementation of the EWMA
method originally proposed by S.W. Roberts based on the normal distribution.
EWMA is part of the family of statistical process control tests.
A named list of class mdsstat_test
object, as follows:
Name of the test run
English description of what was analyzed
Named boolean of whether the test was run. The name contains the run status.
A standardized list of test run results: statistic
for the test statistic, lcl
and ucl
for the 95
confidence bounds, p
for the pvalue, signal
status, and
signal_threshold
.
The test parameters
The data on which the test was run
mds_ts
: EWMA on mds_ts data
default
: EWMA on general data
S. W. Roberts (1959) Control Chart Tests Based on Geometric Moving Averages, Technometrics, 1:3, 239250, DOI: 10.1080/00401706.1959.10489860
1 2 3 4 5 6 7 8 9  # Basic Example
data < data.frame(time=c(1:25), event=as.integer(stats::rnorm(25, 100, 25)))
a1 < ewma(data)
# Example using an mds_ts object
a2 < ewma(mds_ts[[3]])
# Example using a derived rate as the "event"
data < mds_ts[[3]]
data$rate < ifelse(is.na(data$nA), 0, data$nA) / data$exposure
a3 < ewma(data, c(Rate="rate"))

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