Package: mcmcsae 0.7.7
mcmcsae: Markov Chain Monte Carlo Small Area Estimation
Fit multi-level models with possibly correlated random effects using Markov Chain Monte Carlo simulation. Such models allow smoothing over space and time and are useful in, for example, small area estimation.
Authors:
mcmcsae_0.7.7.tar.gz
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mcmcsae.pdf |mcmcsae.html✨
mcmcsae/json (API)
NEWS
# Install 'mcmcsae' in R: |
install.packages('mcmcsae', repos = c('https://hjboonstra.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 8 months agofrom:748b910733. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 25 2024 |
R-4.5-win-x86_64 | OK | Oct 25 2024 |
R-4.5-linux-x86_64 | OK | Oct 25 2024 |
R-4.4-win-x86_64 | OK | Oct 25 2024 |
R-4.4-mac-x86_64 | OK | Oct 25 2024 |
R-4.4-mac-aarch64 | OK | Oct 25 2024 |
R-4.3-win-x86_64 | OK | Oct 25 2024 |
R-4.3-mac-x86_64 | OK | Oct 25 2024 |
R-4.3-mac-aarch64 | OK | Oct 25 2024 |
Exports:%m*v%acceptance_ratesaggrMatrixAR1brtCGCG_controlchol_controlcombine_chainscombine_iterscompute_DICcompute_GMRF_matricescompute_WAICcomputeDesignMatrixcreate_samplercreate_TMVN_samplercrossprod_mvcustomf_binomialf_gammaf_gaussianf_gaussian_gammaf_multinomialf_negbinomialf_poissongengen_controlgenerate_dataget_drawget_meansget_sdsglregiidlabels<-m_directm_Gibbsm_HMCm_HMCZigZagm_softTMVNmaximize_log_lh_pmcmcsae_exampleMCMCsimmecmodel_matrixn_effnchainsndrawsnvarspar_namesplot_coefpr_exppr_fixedpr_gammapr_gigpr_invchisqpr_invwishartpr_MLiGpr_normalR_hatread_drawsregRW1RW2sampler_controlSBC_testseasonsetup_clusterspatialsplinestop_clusterto_draws_arrayto_mcmctransform_dcvfacvreg
Dependencies:abindbackportscheckmateclidistributionalfansigenericsGIGrvggluelatticelifecycleloomagrittrMatrixmatrixStatsnumDerivpillarpkgconfigposteriorRcppRcppEigenrlangtensorAtibbleutf8vctrs
Basic area-level model
Rendered fromarea_level.Rmd
usingknitr::rmarkdown
on Oct 25 2024.Last update: 2023-12-03
Started: 2020-09-01
Basic unit-level models
Rendered fromunit_level.Rmd
usingknitr::rmarkdown
on Oct 25 2024.Last update: 2023-12-03
Started: 2020-09-01
Linear regression, prediction, and survey weighting
Rendered fromlinear_weighting.Rmd
usingknitr::rmarkdown
on Oct 25 2024.Last update: 2023-10-10
Started: 2020-09-01