sim.mc: Markov chain simulation
In mhsmm: Inference for Hidden Markov and Semi-Markov Models
View source: R/hsmm_functions.R
sim.mc R Documentation
Markov chain simulation
Description
Simulates a Markov chain
Usage
sim.mc(init, transition, N)
Arguments
init
The distribution of states at the first time step
transition
The transition probability matrix of the Markov chain
N
The number of observations to simulate
Value
A vector of integers representing the state sequence.
Author(s)
Jared O'Connell jaredoconnell@gmail.com
Examples
p <- matrix(c(.1,.3,.6,rep(1/3,3),0,.5,.5),ncol=3,byrow=TRUE)
init <- rep(1/3,3)
sim.mc(init,p,10)
mhsmm documentation built on Aug. 23, 2023, 9:06 a.m.
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View source: R/hsmm_functions.R
| sim.mc | R Documentation |
Markov chain simulation
Description
Simulates a Markov chain
Usage
sim.mc(init, transition, N)
Arguments
init |
The distribution of states at the first time step |
transition |
The transition probability matrix of the Markov chain |
N |
The number of observations to simulate |
Value
A vector of integers representing the state sequence.
Author(s)
Jared O'Connell jaredoconnell@gmail.com
Examples
p <- matrix(c(.1,.3,.6,rep(1/3,3),0,.5,.5),ncol=3,byrow=TRUE)
init <- rep(1/3,3)
sim.mc(init,p,10)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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