Package: beast 1.1
beast: Bayesian Estimation of Change-Points in the Slope of Multivariate Time-Series
Assume that a temporal process is composed of contiguous segments with differing slopes and replicated noise-corrupted time series measurements are observed. The unknown mean of the data generating process is modelled as a piecewise linear function of time with an unknown number of change-points. The package infers the joint posterior distribution of the number and position of change-points as well as the unknown mean parameters per time-series by MCMC sampling. A-priori, the proposed model uses an overfitting number of mean parameters but, conditionally on a set of change-points, only a subset of them influences the likelihood. An exponentially decreasing prior distribution on the number of change-points gives rise to a posterior distribution concentrating on sparse representations of the underlying sequence, but also available is the Poisson distribution. See Papastamoulis et al (2017) <arxiv:1709.06111> for a detailed presentation of the method.
Authors:
beast_1.1.tar.gz
beast_1.1.zip(r-4.5)beast_1.1.zip(r-4.4)beast_1.1.zip(r-4.3)
beast_1.1.tgz(r-4.4-any)beast_1.1.tgz(r-4.3-any)
beast_1.1.tar.gz(r-4.5-noble)beast_1.1.tar.gz(r-4.4-noble)
beast_1.1.tgz(r-4.4-emscripten)beast_1.1.tgz(r-4.3-emscripten)
beast.pdf |beast.html✨
beast/json (API)
| # Install 'beast' in R: |
| install.packages('beast', repos = c('https://mqbssppe.r-universe.dev', 'https://cloud.r-project.org')) |
- FungalGrowthDataset - Fungal Growth Dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 7 years agofrom:53085f1e14. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 13 2024 |
| R-4.5-win | OK | Sep 13 2024 |
| R-4.5-linux | OK | Sep 13 2024 |
| R-4.4-win | OK | Sep 13 2024 |
| R-4.4-mac | OK | Sep 13 2024 |
| R-4.3-win | OK | Sep 13 2024 |
| R-4.3-mac | OK | Sep 13 2024 |
Exports:beastbirthProbscomplexityPriorcomputeEmpiricalPriorParameterscomputePosteriorParameterscomputePosteriorParametersFreelocalProposallogLikelihoodFullModellogPriormcmcSamplermyUnicodeCharactersnormalizeTime0plot.beast.objectprint.beast.objectproposeThetasimMultiIndNormInvGammasimulateFromPriorsingleLocalProposaltruncatedPoissonupdateNumberOfCutpoints
Dependencies:RColorBrewer
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bayesian Estimation of Change-Points in the Slope of Multivariate Time-Series | beast-package |
| Main function | beast |
| Birth Probabilities | birthProbs |
| Complexity prior distribution | complexityPrior |
| Compute the empirical mean. | computeEmpiricalPriorParameters |
| Compute empirical posterior parameters | computePosteriorParameters |
| Posterior parameters | computePosteriorParametersFree |
| Fungal Growth Dataset | FungalGrowthDataset |
| Move 3.b | localProposal |
| Log-likelihood function. | logLikelihoodFullModel |
| Log-prior. | logPrior |
| MCMC sampler | mcmcSampler |
| Printing | myUnicodeCharacters |
| Zero normalization | normalizeTime0 |
| Plot function | plot.beast.object |
| Print function | print.beast.object |
| Move 2 | proposeTheta |
| Prior random numbers | simMultiIndNormInvGamma |
| Generate change-points according to the prior | simulateFromPrior |
| Move 3.b | singleLocalProposal |
| Truncated Poisson pdf | truncatedPoisson |
| Move 1 | updateNumberOfCutpoints |
