| ctmcd-package {ctmcd} | R Documentation |
Estimating the Parameters of a Continuous-Time Markov Chain from Discrete-Time Data
Description
Functions for estimating Markov generator matrices from discrete-time observations.
Author(s)
Marius Pfeuffer [aut, cre], Greig Smith [ctb], Goncalo dos Reis [ctb], Linda Moestel [ctb], Matthias Fischer [ctb]
Maintainer: Marius Pfeuffer <marius.pfeuffer@fau.de>
References
M. Pfeuffer: ctmcd: An R Package for Estimating the Parameters of a Continuous-Time Markov Chain from Discrete-Time Data. The R Journal 9(2):127-141, 2017
M. Pfeuffer. Generator Matrix Approximation Based on Discrete-Time Rating Migration Data. Master Thesis, Ludwig Maximilian University of Munich, 2016
R. B. Israel et al.: Finding Generators for Markov Chains via Empirical Transition Matrices, with Applications to Credit Ratings. Mathematical Finance 11(2):245-265, 2001
E. Kreinin and M. Sidelnikova: Regularization Algorithms for Transition Matrices. Algo Research Quarterly 4(1):23-40, 2001
M. Bladt and M. Soerensen: Statistical Inference for Discretely Observed Markov Jump Processes. Journal of the Royal Statistical Society B 67(3):395-410, 2005
Examples
data(tm_abs)
## Maximum Likelihood Generator Matrix Estimate
gm0=matrix(1,8,8)
diag(gm0)=0
diag(gm0)=-rowSums(gm0)
gm0[8,]=0
gmem=gm(tm_abs,te=1,method="EM",gmguess=gm0)
plot(gmem)
## Confidence Interval
ciem=gmci(gmem,alpha=0.05)
plot(ciem)