Package: MisRepARMA 0.2.0
MisRepARMA: Misreported Time Series Analysis
Provides a simple and trustworthy methodology for the analysis of misreported continuous time series using either a frequentist (bootstrap-based EM algorithm) or a Bayesian (MCMC via JAGS) approach. The frequentist method is described in Morina et al. (2021) <doi:10.1038/s41598-021-02620-5>. The Bayesian extension fits the same ARMA model with misreporting structure using a full posterior distribution, providing credible intervals and DIC for model comparison, as described in Morina et al. (2024) <doi:10.1101/2024.02.26.24303373>.
Authors:
MisRepARMA_0.2.0.tar.gz
MisRepARMA_0.2.0.zip(r-4.7)MisRepARMA_0.2.0.zip(r-4.6)MisRepARMA_0.2.0.zip(r-4.5)
MisRepARMA_0.2.0.tgz(r-4.6-any)MisRepARMA_0.2.0.tgz(r-4.5-any)
MisRepARMA_0.2.0.tar.gz(r-4.7-any)MisRepARMA_0.2.0.tar.gz(r-4.6-any)
MisRepARMA_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
MisRepARMA/json (API)
| # Install 'MisRepARMA' in R: |
| install.packages('MisRepARMA', repos = c('https://dmorinya.r-universe.dev', 'https://cloud.r-project.org')) |
- jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
- c++– GNU Standard C++ Library v3
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:b0751118d7. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 174 | ||
| source / vignettes | OK | 250 | ||
| linux-release-x86_64 | OK | 172 | ||
| macos-release-arm64 | OK | 146 | ||
| macos-oldrel-arm64 | OK | 158 | ||
| windows-devel | OK | 156 | ||
| windows-release | OK | 156 | ||
| windows-oldrel | OK | 120 | ||
| wasm-release | OK | 131 |
Exports:estimateestimate_bayesfitMisRepARMAprint.summary.fitMisRepARMAran.genfreconstructsummary.fitMisRepARMA
Dependencies:abindaskpassbase64encbootbslibcachemclicodacpp11crosstalkcurldata.tabledigestdplyrevaluatefarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonlitekernlabknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixmemoisemimemixtoolsnlmeopensslotelpillarpkgconfigplotlypromisespurrrquadprogquantmodR2jagsR2WinBUGSR6rappdirsRColorBrewerRcpprjagsrlangrmarkdownS7sassscalessegmentedstringistringrsurvivalsystibbletidyrtidyselecttinytextseriesTTRutf8vctrsviridisLitewithrxfunxtsyamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Misreported time series analysis | MisRepARMA-package MisRepARMA |
| Fit ARMA model to misreported time series data | fitMisRepARMA |
| Reconstruct the most likely series | reconstruct |
