Package: bliss 1.1.1
Paul-Marie Grollemund
bliss: Bayesian Functional Linear Regression with Sparse Step Functions
A method for the Bayesian functional linear regression model (scalar-on-function), including two estimators of the coefficient function and an estimator of its support. A representation of the posterior distribution is also available. Grollemund P-M., Abraham C., Baragatti M., Pudlo P. (2019) <doi:10.1214/18-BA1095>.
Authors:
bliss_1.1.1.tar.gz
bliss_1.1.1.tar.gz(r-4.7-arm64)bliss_1.1.1.tar.gz(r-4.7-x86_64)bliss_1.1.1.tar.gz(r-4.6-arm64)bliss_1.1.1.tar.gz(r-4.6-x86_64)
bliss_1.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
bliss/json (API)
NEWS
| # Install 'bliss' in R: |
| install.packages('bliss', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/pmgrollemund/bliss/issues
- data1 - A list of data
- param1 - A list of param for bliss model
- res_bliss1 - A result of the BliSS method
Last updated from:80cc074738. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 144 | ||
| linux-devel-x86_64 | OK | 127 | ||
| source / vignettes | OK | 223 | ||
| linux-release-arm64 | OK | 146 | ||
| linux-release-x86_64 | OK | 142 | ||
| wasm-release | OK | 118 |
Exports:%between%BIC_model_choiceBliss_Gibbs_SamplerBliss_Simulated_Annealingbuild_Fourier_basischange_gridchoose_betacompute_beta_posterior_densitycompute_beta_samplecompute_random_walkcompute_starting_point_sanncorr_matrixdetermine_intervalsdo_need_to_reducedposteriorfit_Blissimage_Blissintegrate_trapezeinterpretation_plotlines_blisspdexppost_treatment_blisspredict_blisspredict_bliss_distributionprintblissreduce_xsigmoidsigmoid_sharpsimsim_xsupport_estimation
Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecycleMASSR6RColorBrewerRcppRcppArmadilloRcppProgressrlangS7scalesvctrsviridisLitewithr
