Last data update: 2014.03.03
R: Plotting the relative error for the mean value functions for...
Plotting the relative error for the mean value functions for all models
Description
total.plot
plots the relative error for the the mean value function for all
models into one window.
Usage
rel.plot(duane.par1, duane.par2, lit.par1, lit.par2, lit.par3, mor.par1,
mor.par2, musa.par1, musa.par2, t, linear = T, ymin, ymax,
xlab = "time", ylab = "relative error", main = NULL)
Arguments
duane.par1
parameter value for rho
for Duane model
duane.par2
parameter value for theta
for Duane model
lit.par1
parameter value for theta0
for Littlewood-Verall model
lit.par2
parameter value for theta1
for Littlewood-Verall model
lit.par3
parameter value for rho
for Littlewood-Verall model
mor.par1
parameter value for D
for Moranda-Geometric model
mor.par2
parameter value for theta
for Moranda-Geometric model
musa.par1
parameter value for theta0
for Musa-Okumoto model
musa.par2
parameter value for theta1
for Musa-Okumoto model
t
time between failure data
linear
logical. Should the linear or the quadratic form of the mean value
function for the Littlewood-Verrall model be used of computation?
If TRUE
, which is the default, the linear form of the mean
value function is used.
ymin
the minimal y limit of the plot
ymax
the maximal y limit of the plot
xlab
a title for the x axis
ylab
a title for the y axis
main
an overall title for the plot
Details
This function gives a plot of the relative error for the mean value functions for
all models, this is
mbox{relative error} = frac{μ(t_i) - i}{i}, i = 1, 2, ...,
where μ(t) is a mean value function and i is the number of failures.
Here
the estimated parameter values, which are obtained by using duane
,
littlewood.verall
, moranda.geometric
und
musa.okumoto
can be put in. Internally the functions
mvf.duane
, mvf.ver.lin
, mvf.ver.quad
,
mvf.mor
and mvf.musa
are used to get the mean value
functions for all models.
Value
A graph of the relative error for the mean value functions for all models.
Author(s)
Andreas Wittmann andreas_wittmann@gmx.de
References
J.D. Musa, A. Iannino, and K. Okumoto. Software Reliability: Measurement,
Prediction, Application . McGraw-Hill, 1987.
Michael R. Lyu. Handbook of Software Realibility Engineering . IEEE Computer
Society Press, 1996.
http://www.cse.cuhk.edu.hk/~lyu/book/reliability/
See Also
duane.plot
, littlewood.verall.plot
,
moranda.geometric.plot
, musa.okumoto.plot
,
total.plot
Examples
# time between-failure-data from DACS Software Reliability Dataset
# homepage, see system code 1. Number of failures is 136.
t <- c(3, 30, 113, 81, 115, 9, 2, 20, 20, 15, 138, 50, 77, 24,
108, 88, 670, 120, 26, 114, 325, 55, 242, 68, 422, 180,
10, 1146, 600, 15, 36, 4, 0, 8, 227, 65, 176, 58, 457,
300, 97, 263, 452, 255, 197, 193, 6, 79, 816, 1351, 148,
21, 233, 134, 357, 193, 236, 31, 369, 748, 0, 232, 330,
365, 1222, 543, 10, 16, 529, 379, 44, 129, 810, 290, 300,
529, 281, 160, 828, 1011, 445, 296, 1755, 1064, 1783,
860, 983, 707, 33, 868, 724, 2323, 2930, 1461, 843, 12,
261, 1800, 865, 1435, 30, 143, 108, 0, 3110, 1247, 943,
700, 875, 245, 729, 1897, 447, 386, 446, 122, 990, 948,
1082, 22, 75, 482, 5509, 100, 10, 1071, 371, 790, 6150,
3321, 1045, 648, 5485, 1160, 1864, 4116)
duane.par1 <- duane(t)$rho
duane.par2 <- duane(t)$theta
lit.par1 <- littlewood.verall(t, linear = TRUE)$theta0
lit.par2 <- littlewood.verall(t, linear = TRUE)$theta1
lit.par3 <- littlewood.verall(t, linear = TRUE)$rho
mor.par1 <- moranda.geometric(t)$D
mor.par2 <- moranda.geometric(t)$theta
musa.par1 <- musa.okumoto(t)$theta0
musa.par2 <- musa.okumoto(t)$theta1
rel.plot(duane.par1, duane.par2, lit.par1, lit.par2, lit.par3, mor.par1,
mor.par2, musa.par1, musa.par2, t, linear = TRUE, ymin = -1,
ymax = 2.5, xlab = "time (in seconds)", main = "relative error")
## Not run:
## rel.plot(duane.par1, duane.par2, lit.par1, lit.par2, lit.par3, mor.par1,
## mor.par2, musa.par1, musa.par2, t, linear = TRUE,
## xlab = "time (in seconds)", main = "relative error")
## End(Not run)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(Reliability)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/Reliability/rel.plot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: rel.plot
> ### Title: Plotting the relative error for the mean value functions for all
> ### models
> ### Aliases: rel.plot
> ### Keywords: models
>
> ### ** Examples
>
> # time between-failure-data from DACS Software Reliability Dataset
> # homepage, see system code 1. Number of failures is 136.
> t <- c(3, 30, 113, 81, 115, 9, 2, 20, 20, 15, 138, 50, 77, 24,
+ 108, 88, 670, 120, 26, 114, 325, 55, 242, 68, 422, 180,
+ 10, 1146, 600, 15, 36, 4, 0, 8, 227, 65, 176, 58, 457,
+ 300, 97, 263, 452, 255, 197, 193, 6, 79, 816, 1351, 148,
+ 21, 233, 134, 357, 193, 236, 31, 369, 748, 0, 232, 330,
+ 365, 1222, 543, 10, 16, 529, 379, 44, 129, 810, 290, 300,
+ 529, 281, 160, 828, 1011, 445, 296, 1755, 1064, 1783,
+ 860, 983, 707, 33, 868, 724, 2323, 2930, 1461, 843, 12,
+ 261, 1800, 865, 1435, 30, 143, 108, 0, 3110, 1247, 943,
+ 700, 875, 245, 729, 1897, 447, 386, 446, 122, 990, 948,
+ 1082, 22, 75, 482, 5509, 100, 10, 1071, 371, 790, 6150,
+ 3321, 1045, 648, 5485, 1160, 1864, 4116)
>
> duane.par1 <- duane(t)$rho
> duane.par2 <- duane(t)$theta
>
> lit.par1 <- littlewood.verall(t, linear = TRUE)$theta0
> lit.par2 <- littlewood.verall(t, linear = TRUE)$theta1
> lit.par3 <- littlewood.verall(t, linear = TRUE)$rho
>
> mor.par1 <- moranda.geometric(t)$D
> mor.par2 <- moranda.geometric(t)$theta
>
> musa.par1 <- musa.okumoto(t)$theta0
> musa.par2 <- musa.okumoto(t)$theta1
>
> rel.plot(duane.par1, duane.par2, lit.par1, lit.par2, lit.par3, mor.par1,
+ mor.par2, musa.par1, musa.par2, t, linear = TRUE, ymin = -1,
+ ymax = 2.5, xlab = "time (in seconds)", main = "relative error")
>
> ## Not run:
> ##D ## rel.plot(duane.par1, duane.par2, lit.par1, lit.par2, lit.par3, mor.par1,
> ##D ## mor.par2, musa.par1, musa.par2, t, linear = TRUE,
> ##D ## xlab = "time (in seconds)", main = "relative error")
> ## End(Not run)
>
>
>
>
>
> dev.off()
null device
1
>