Package: ctmcd 1.4.4

Marius Pfeuffer

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

Estimation of Markov generator matrices from discrete-time observations. The implemented approaches comprise diagonal and weighted adjustment of matrix logarithm based candidate solutions as in Israel (2001) <doi:10.1111/1467-9965.00114> as well as a quasi-optimization approach. Moreover, the expectation-maximization algorithm and the Gibbs sampling approach of Bladt and Sorensen (2005) <doi:10.1111/j.1467-9868.2005.00508.x> are included.

Authors:Marius Pfeuffer [aut, cre], Greig Smith [ctb], Goncalo dos Reis [ctb], Linda Moestel [ctb], Matthias Fischer [ctb]

ctmcd_1.4.4.tar.gz
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ctmcd.pdf |ctmcd.html✨
ctmcd/json (API)

# Install 'ctmcd' in R:
install.packages('ctmcd', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • tm_abs - Single Year Corporate Credit Rating Transititions

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

23 exports 2 stars 0.23 score 7 dependencies 23 scripts 427 downloads

Last updated 7 months agofrom:70686c4f30. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 07 2024
R-4.5-linux-x86_64OKSep 07 2024

Exports:ciEMBSciEMoFIciEMSdRciGSctmcdlogLikgmgm.defaultgmcigmci.defaultgmDAgmEMgmGSgmQOgmWAplot.gmplot.gmciplotMprint.gmprint.gmcirNijTRiT_ModRejrNijTRiT_Unifsummary.gmtmci

Dependencies:codaexpmlatticeMatrixnumDerivRcppRcppArmadillo

A ctmcd Guide

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Last update: 2018-06-03
Started: 2016-08-16

ctmcd: An R Package for Estimating the Parameters of a Continuous-Time Markov Chain from Discrete-Time Data

Rendered fromRJ-2017-038.pdf.asisusingR.rsp::asison Sep 07 2024.

Last update: 2017-10-09
Started: 2017-10-09