simEd (version 2.0.0)

sdTPS: Standard Deviation of Time-Persistent Statistics (TPS)

Description

Computes the sample standard deviation of a time-persistent statistic.

Usage

sdTPS(times = NULL, numbers = NULL)

Arguments

times

A numeric vector of non-decreasing time observations

numbers

A numeric vector containing the values of the time-persistent statistic between the time observation

Value

Computes the sample standard deviation of the time-persistent statistic provided.

Details

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 variance is the area under the square of the step-function created by the values in numbers between the first and last element in times divided by the length of the observation period, less the square of the sample mean. The sample standard deviation is the square root of the sample variance.

Examples

# NOT RUN {
 times  <- c(1,2,3,4,5)
 counts <- c(1,2,1,1,2)
 meanTPS(times, counts)
 sdTPS(times, counts)

 output <- ssq(seed = 54321, maxTime = 1000, saveServerStatus = TRUE)
 utilization <- meanTPS(output$serverStatusT, output$serverStatusN)
 sdServerStatus <- sdTPS(output$serverStatusT, output$serverStatusN)

 # compute and graphically display mean and sd of number in system vs time
 output <- ssq(maxArrivals = 60, seed = 54321, saveAllStats = TRUE)
 plot(output$numInSystemT, output$numInSystemN, type = "s", bty = "l",
    las = 1, xlab = "time", ylab = "number in system")
 meanSys <- meanTPS(output$numInSystemT, output$numInSystemN)
 sdSys   <- sdTPS(output$numInSystemT, output$numInSystemN)
 abline(h = meanSys, lty = "solid", col = "red", lwd = 2)
 abline(h = c(meanSys - sdSys, meanSys + sdSys),
    lty = "dashed", col = "red", lwd = 2)

# }