gmQO: Quasi-Optimization

In ctmcd: Estimating the Parameters of a Continuous-Time Markov Chain from Discrete-Time Data

Quasi-Optimization

Description

Function for deriving a Markov generator matrix estimate based on the quasi-optimization procedure of Kreinin and Sidelnikova, 2001

Usage

gmQO(tmrel, te, logmethod = "Eigen")

Arguments

tmrel	matrix of relative transition frequencies
te	time elapsed in transition process
logmethod	method for computation of matrix logarithm, by default eigendecomposition is chosen (see ?logm from expm package for more information)

Details

From the set of possible Markov generator matrices, the one is chosen which is closest to a matrix logarithm based candidate solution in terms of sum of squared deviations.

Value

generator matrix estimate

Author(s)

Marius Pfeuffer

References

E. Kreinin and M. Sidelnikova: Regularization Algorithms for Transition Matrices. Algo Research Quarterly 4(1):23-40, 2001

Examples

data(tm_abs)
## Derive matrix of relative transition frequencies
data(tm_abs)
tm_rel=rbind((tm_abs/rowSums(tm_abs))[1:7,],c(rep(0,7),1))

## Derive quasi optimization generator matrix estimate
gmqo=gmQO(tm_rel,1)
gmqo

ctmcd documentation built on May 31, 2023, 7:55 p.m.