simulate.carms {CARMS} | R Documentation |

## Generate a simulation of a carms object.

### Description

This function calls for the simulation on a completed carms object.

### Usage

```
simulate.carms(x, solution, mission_time, intervals=50, cycles=2000)
```

### Arguments

`x` |
A completed |

`solution` |
A string of "rk", "bd", or "chain" indicating the method of obtaining the simulation solution. Although not intended for production work, it is possible to enter a string of "chain_R" to execute the formative R code for the stochastic chain solution. |

`mission_time` |
A time value for the extent of mission history for the simulation |

`intervals` |
An integer value for the number of intervals over the mission history to calculate the simulation. |

`cycles` |
An integer value (usually in the thousands) impacting the number of simulations run only when using the chain solution. |

### Details

It was chosen not to register this functionThis function, due to differences in fundimental arguments with stats::simulate.

### Value

This function returns a matrix of probabilities for each state at each time step to the carms$simulation list element.

### References

Jan Pukite and Paul Pukite (1998), "Modeling for Reliability Analysis", IEEE Press, New York

William J. Stewart (1994), "Introduction to the numerical solution of Markov chains", Princeton University Press, Princeton

### Examples

```
SiSimpl<-carms.make(title="Parallel Identical components", diagram_grid=c(5,8))
SiSimpl<-carms.state(SiSimpl, prob=1, name="P1", size=7, h2w=14/20, position=c(2,3) )
SiSimpl<-carms.state(SiSimpl, prob=0, name="P2", size=7, h2w=14/20, position=c(6,3) )
SiSimpl<-carms.base(SiSimpl, 1, time_units="hours", description="Failure rate")
SiSimpl<-carms.arrow(SiSimpl, from=1, to=2, rate="B1",label="B1")
SiSimpl<-simulate.carms(SiSimpl, solution="rk", mission_time=200)
```

*CARMS*version 1.0.1 Index]