Plotting the mean value functions for all models

Description

total.plot plots the mean value function for all models and the raw data into one window.

Usage

total.plot(duane.par1, duane.par2, lit.par1, lit.par2, lit.par3, mor.par1, 
           mor.par2, musa.par1, musa.par2, t, linear = T, xlab = "time", 
           ylab = "Cumulated failures and estimated mean value functions", 
           main = NULL)

Arguments

Details

This function gives a plot of the mean value functions for all models. 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 mean value functions for all models and of the raw data.

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

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

total.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 = "all models")

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/total.plot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: total.plot
> ### Title: Plotting the mean value functions for all models
> ### Aliases: total.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
> 
> total.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 = "all models")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>