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Computes the sample quantiles of a time-persistent statistic corresponding to the given probabilities.
quantileTPS(times = NULL, numbers = NULL, probs=c(0,0.25,0.5,0.75,1.0))
a numeric vector of non-decreasing time observations
a numeric vector containing the values of the time-persistent statistic between the time observations
a numeric vector of probabilities with values in [0,1]
Computes the sample quantiles of the time-persistent statistic provided.
The lengths of times
and numbers
either must be the same,
or times
may have one more entry than numbers
(interval endpoints
vs. interval counts). The sample quantiles are calculated by determining
the length of time spent in each state, sorting these times, then calculating
the quantiles associated with the values in the prob
vector in the
same fashion as one would calculate quantiles associated with a univariate
discrete probability distribution.
# NOT RUN {
times <- c(1,2,3,4,5)
counts <- c(1,2,1,1,2)
meanTPS(times, counts)
sdTPS(times, counts)
quantileTPS(times, counts)
output <- ssq(seed = 54321, maxTime = 1000, saveNumInSystem = TRUE)
utilization <- meanTPS(output$numInSystemT, output$numInSystemN)
sdServerStatus <- sdTPS(output$numInSystemT, output$numInSystemN)
quantileServerStatus <- quantileTPS(output$numInSystemT, output$numInSystemN)
# compute and graphically display quantiles of number in system vs time
output <- ssq(maxArrivals = 60, seed = 54321, saveAllStats = TRUE)
quantileSys <- quantileTPS(output$numInSystemT, output$numInSystemN)
plot(output$numInSystemT, output$numInSystemN, type = "s", bty = "l", las = 1,
xlab = "time", ylab = "number in system")
labels <- c("0%", "25%", "50%", "75%", "100%")
mtext(text = labels, side = 4, at = quantileSys, las = 1, col = "red")
abline(h = quantileSys, lty = "dashed", col = "red", lwd = 2)
# }
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