Package: thamesblock 0.1.0
thamesblock: Truncated Harmonic Mean Estimator of the Marginal Likelihood for Block Models
Implements the truncated harmonic mean estimator (THAMES) and other estimators of the reciprocal marginal likelihood for block models. This is done via reciprocal importance sampling, using posterior samples and unnormalized log posterior values. For further information see Metodiev, Perrot-Dockès, Fouetilou, Latouche & Raftery (2026).
Authors:
thamesblock_0.1.0.tar.gz
thamesblock_0.1.0.zip(r-4.7)thamesblock_0.1.0.zip(r-4.6)thamesblock_0.1.0.zip(r-4.5)
thamesblock_0.1.0.tgz(r-4.6-any)thamesblock_0.1.0.tgz(r-4.5-any)
thamesblock_0.1.0.tar.gz(r-4.7-any)thamesblock_0.1.0.tar.gz(r-4.6-any)
thamesblock_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
thamesblock/json (API)
| # Install 'thamesblock' in R: |
| install.packages('thamesblock', repos = c('https://m-metodiev.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:131d7772be. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 149 | ||
| source / vignettes | OK | 129 | ||
| linux-release-x86_64 | OK | 100 | ||
| macos-release-arm64 | OK | 90 | ||
| macos-oldrel-arm64 | OK | 75 | ||
| windows-devel | OK | 106 | ||
| windows-release | OK | 100 | ||
| windows-oldrel | OK | 93 | ||
| wasm-release | OK | 108 |
Exports:ChibPartitioncompute_nobile_identityharmonic_mean_estimatorrisvbthamesblock
Dependencies:combinatlabel.switchinglatticelpSolveMatrixmclustwithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Computes the ChibPartition estimator | ChibPartition |
| Nobile's identity for the marginal likelihood | compute_nobile_identity |
| Computes the harmonic mean estimator | harmonic_mean_estimator |
| Computes the RISVB estimator for block models | risvb |
| Computes the THAMES for the stochastic block model | thamesblock |
