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

In simEd: Simulation Education

Standard Deviation of Time-Persistent Statistics (TPS)

Description

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

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

Details

The lengths of \code{times} and \code{numbers} either must be
the same, or \code{times} may have one more entry than \code{numbers}
(interval endpoints vs. interval counts). The sample variance is the
area under the square of the step-function created by the values in
\code{numbers} between the first and last element in \code{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.

Value

the sample standard deviation of the time-persistent function provided

Author(s)

Barry Lawson ([e-mail]),
Larry Leemis ([e-mail]),
Vadim Kudlay ([e-mail])

Examples

 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 = 100, 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)

simEd documentation built on Nov. 27, 2023, 1:07 a.m.