https://github.com/cran/ctmcd
Revision 6ed185ca499d9978697004778a4feb44cca5d8fc authored by Marius Pfeuffer on 26 May 2022, 13:30:04 UTC, committed by cran-robot on 26 May 2022, 13:30:04 UTC
1 parent 6311906
Tip revision: 6ed185ca499d9978697004778a4feb44cca5d8fc authored by Marius Pfeuffer on 26 May 2022, 13:30:04 UTC
version 1.4.2
version 1.4.2
Tip revision: 6ed185c
rNijTRiT_Unif.Rd
\name{rNijTRiT_Unif}
\alias{rNijTRiT_Unif}
\title{
C++ Based Uniformization Sampling
}
\description{
Function for generating initial and endpoint-conditioned Markov process sampling paths for a given discrete-time transition matrix
}
\usage{
rNijTRiT_Unif(tmabs, te, gm, tpm)
}
\arguments{
\item{tmabs}{
matrix of absolute transition frequencies
}
\item{te}{
time elapsed in transition process
}
\item{gm}{
generator matrix
}
\item{tpm}{
discrete-time transition probability matrix, matrix exponential of gm
}
}
\details{
Function for the simulation of paths from an endpoint-conditioned Markov process. Returns number of transitions NijT and cumulative holding times RiT.
}
\references{
J. Fintzi: R Package ECctmc, 2016.
A. Hobolth and E. A. Stone: Simulation from Endpoint-Conditioned, Continuous-Time Markov Chains on a Finite State Space, with Applications to Molecular Evolution. Annals of Applied Statistics 3(3):1204-1231, 2009
}
\author{
Jon Fintzi, Marius Pfeuffer
}
\examples{
data(tm_abs)
## Generator Matrix
gm=matrix(1,8,8)
diag(gm)=0
diag(gm)=-rowSums(gm)
gm[8,]=0
## Transition Probability Matrix
library(expm)
te=1
tpm=expm(gm*te)
rNijTRiT_Unif(tm_abs,te,gm,tpm)
}
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