Description Usage Arguments Value Examples
Control Charts made easy. Calculates Control Systems for a time series. The current distribution uses the following Control Rules to define systems: 1. Mean Rule: N continuous points above or below mean. See points.vs.avg argument. 2. Out of Control Points Rule: Points above or below 3 Standard Deviation are excluded from calculations.
1 2 |
data |
The input Data Frame. |
dates |
Column name for date or ordering variable. |
values |
Column name for data points values. Class should be numeric, if not, will attempt to coerce. |
points.vs.avg |
For Mean Rule, establishes how many continuous points should be above or below mean to define a system. Default to 6. |
date.type |
States if observations are based on dates. Defaults to TRUE. If TRUE, will attempt to coerce to a date format using extensive use of lubridate package dates formats. |
already.ordered |
Tells the function if the data is already ordered. Defaults to FALSE. The function will attempt to order it. |
The function will return a list object with class ccpoints.
A list including the data frame with the system points, and column names of the series.
The data frame will include the submited series and the following new columns:
data.mean: the mean value for each system
data.ll: the lower standard deviation of each system
data.ul: the upper standard deviation of each system
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | # Create a random time series
set.seed(154)
time.series <- data.frame(t.dates = seq.Date(as.Date("2014-02-01"), as.Date("2016-08-01"), "month"),
t.values = c(
seq(0.1, 0.8, by = 0.1) * runif(8) + 3,
seq(0.1, 0.7, by = 0.1) * runif(7) + 4,
seq(0.1, 0.7, by = 0.1) * runif(7) + 5,
seq(0.1, 0.4, by = 0.1) * runif(4) + 4,
seq(0.1, 0.5, by = 0.1) * runif(5) + 4)
)
# Execute function
control.chart.data <- ccpoints(time.series, "t.dates", "t.values")
print(control.chart.data)
# To extract only the data frame
control.chart.data[["data"]]
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