# XmR charts for several measures at the same day/month

Xmr charts are often used in statistical process control (see for example). They make sense, but I wonder what one does, if one has several measure per day/month etc. Should one just use the average (e.g. arithmetic mean)?

This code taken from here simulates 12 measurements, one for each month:

library(ggplot2)
library(ggQC)

set.seed(5555)
Golden_Egg_df <- data.frame(month=1:12,
egg_diameter = rnorm(n = 12, mean = 1.5, sd = 0.2)
)
Golden_Egg_df\$egg_diameter[3] <- 2.5

options(repr.plot.width = 5, repr.plot.height = 5)
XmR_Plot <- ggplot(Golden_Egg_df, aes(x = month, y = egg_diameter)) +
geom_point() + geom_line() +
stat_QC(method = "XmR")

XmR_Plot


• As I read your question, you may consider removing the "change-point" and "structural-change" tags and add the control-chart tag. Or is there truly a change point to a new function? Dec 26 '20 at 22:11
• I posted an answer assuming that all data points are sampled from a univariate time series. If it is multivariate (the data points are generated from different processes) please update the question accordingly. Dec 26 '20 at 22:20
• @JonasLindeløv thanks. I added an answer. I think I need to edit the question as my time series may be multivariate. I have several people doing the same job (THE? process). Every other date a person completes a job and creates a KPI. That's why I can have several values per day. Dec 27 '20 at 6:19
• I updated my answer so that it hopefully addresses these questions. Dec 28 '20 at 20:57