{ "_id": "6ac4f115f511ae58c09a3525", "Package": "spBPS", "Title": "Bayesian Predictive Stacking for Scalable Geospatial Transfer\nLearning", "Version": "2.0-1", "Authors@R": "c(\nperson(\"Luca\", \"Presicce\", role = c(\"aut\", \"cre\"), email = \"l.presicce@campus.unimib.it\", comment = c(ORCID = \"0009-0005-7062-3523\")),\nperson(\"Sudipto\", \"Banerjee\", role = \"aut\"))", "Maintainer": "Luca Presicce ", "Author": "Luca Presicce [aut, cre]\n(), Sudipto Banerjee\n[aut]", "Description": "Provides functions for Bayesian Predictive Stacking within\nthe Bayesian transfer learning framework for geospatial\nartificial systems, as introduced in \"Bayesian Transfer\nLearning for Artificially Intelligent Geospatial Systems: A\nPredictive Stacking Approach\" (Presicce and Banerjee, 2025)\n. This methodology enables\nefficient Bayesian geostatistical modeling, utilizing\npredictive stacking to improve inference across spatial\ndatasets. The core functions leverage 'C++' for\nhigh-performance computation, making the framework well-suited\nfor large-scale spatial data analysis in parallel and\ndistributed computing environments. Designed for scalability,\nit allows seamless application in computationally demanding\nscenarios.", "Config/testthat/edition": "3", "License": "GPL (>= 3)", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "URL": "https://lucapresicce.github.io/spBPS/", "Config/pak/sysreqs": "cmake libgmp3-dev make pkg-config libclang-dev", "Repository": "https://lucapresicce.r-universe.dev", "Date/Publication": "2026-05-07 16:24:47 UTC", "RemoteUrl": "https://github.com/lucapresicce/spbps", "RemoteRef": "HEAD", "RemoteSha": "7881eacb2894b4e203386e7e13a584429683d5a1", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-10-06 12:52:39 UTC", "User": "root" }, "_user": "lucapresicce", "_type": "src", "_file": "spBPS_2.0-1.tar.gz", "_fileid": "https://r2.ropensci.org/e19be6dfc9f5cd92460d5df07baffac50bc5e92eae22652150c887a2b3fd3e43", "_filesize": 762779, "_sha256": "e19be6dfc9f5cd92460d5df07baffac50bc5e92eae22652150c887a2b3fd3e43", "_expires": "2027-01-14T13:01:07.000Z", "_created": "2026-10-06T12:52:39.000Z", "_published": "2026-10-06T13:01:09.416Z", "_jobs": [ { "job": 112279146245, "time": 175, "config": "linux-devel-arm64", "r": "4.7.0", "check": "OK", "artifact": "11415701193" }, { "job": 112279146277, "time": 185, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11414642249" }, { "job": 112279146382, "time": 162, "config": "linux-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "11415656165" }, { "job": 112279146417, "time": 199, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11415806116" }, { "job": 112279146227, "time": 244, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "11414716862" }, { "job": 112279146252, "time": 340, "config": "macos-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "11415351933" }, { "job": 112279146487, "time": 223, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "11415431224" }, { "job": 112279146201, "time": 419, "config": "macos-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11414539444" }, { "job": 112277015933, "time": 301, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "11414756623" }, { "job": 112279146059, "time": 167, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "11415326423" }, { "job": 112279146473, "time": 410, "config": "windows-devel-arm64", "r": "4.7.0", "check": "OK", "artifact": "11415431778" }, { "job": 112279146200, "time": 163, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11414951565" }, { "job": 112279146309, "time": 141, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "11415726065" }, { "job": 112279146454, "time": 400, "config": "windows-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "11415142149" }, { "job": 112279146292, "time": 201, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11414642319" } ], "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596", "_status": "success", "_upstream": "https://github.com/lucapresicce/spbps", "_commit": { "id": "7881eacb2894b4e203386e7e13a584429683d5a1", "author": "lucapresicce ", "committer": "lucapresicce ", "message": "CRAN resubmission v2.0-1\n", "time": 1778171087 }, "_maintainer": { "name": "Luca Presicce", "email": "l.presicce@campus.unimib.it", "login": "lucapresicce", "description": "PhD student in Statistics @unimib\nVisiting researcher @ucla", "uuid": 77741338, "orcid": "0009-0005-7062-3523" }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 1.8.0", "role": "Depends" }, { "package": "Rcpp", "role": "LinkingTo" }, { "package": "RcppArmadillo", "role": "LinkingTo" }, { "package": "Rcpp", "role": "Imports" }, { "package": "CVXR", "version": ">= 1.8.1", "role": "Imports" }, { "package": "mniw", "role": "Imports" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "abind", "role": "Suggests" }, { "package": "mvnfast", "role": "Suggests" }, { "package": "ECOSolveR", "role": "Suggests" }, { "package": "foreach", "role": "Suggests" }, { "package": "parallel", "role": "Suggests" }, { "package": "doParallel", "role": "Suggests" }, { "package": "tictoc", "role": "Suggests" }, { "package": "MBA", "role": "Suggests" }, { "package": "RColorBrewer", "role": "Suggests" }, { "package": "classInt", "role": "Suggests" }, { "package": "sp", "role": "Suggests" }, { "package": "fields", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" } ], "_owner": "lucapresicce", "_selfowned": true, "_usedby": 1, "_updates": [ { "week": "2025-48", "n": 2 }, { "week": "2026-12", "n": 5 }, { "week": "2026-19", "n": 1 } ], "_tags": [ { "name": "v1.0-1", "date": "2026-03-19" } ], "_stars": 0, "_contributors": [ { "user": "lucapresicce", "count": 21, "uuid": 77741338 } ], "_userbio": { "uuid": 77741338, "type": "user", "name": "Luca Presicce", "followers": 3, "description": "PhD student in Statistics @UniMiB\r\nVisiting researcher @UCLA" }, "_downloads": { "count": 448, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/spBPS" }, "_devurl": "https://github.com/lucapresicce/spbps", "_pkgdown": "https://lucapresicce.github.io/spBPS/", "_searchresults": 19, "_topics": [ "openblas", "cpp", "openmp" ], "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/manual.pdf", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "extra/spBPS.html" ], "_homeurl": "https://github.com/lucapresicce/spbps", "_realowner": "lucapresicce", "_cranurl": true, "_releases": [ { "version": "0.0-4", "date": "2024-10-25" }, { "version": "1.0-1", "date": "2026-03-19" }, { "version": "2.0-1", "date": "2026-05-14" } ], "_exports": [ "bayesMvLMconjugate", "pred_bayesMvLMconjugate", "spBPS", "subset_data" ], "_help": [ { "page": "arma_dist", "title": "Compute the Euclidean distance matrix", "topics": [ "arma_dist" ] }, { "page": "bayesMvLMconjugate", "title": "Gibbs sampler for Conjugate Bayesian Multivariate Linear Models", "topics": [ "bayesMvLMconjugate" ] }, { "page": "BPS_combine", "title": "Combine subset models wiht BPS", "topics": [ "BPS_combine" ] }, { "page": "BPS_post_MvT", "title": "Perform the BPS sampling from posterior and posterior predictive given a set of stacking weights", "topics": [ "BPS_post_MvT" ] }, { "page": "BPS_postdraws_MvT", "title": "Compute the BPS posterior samples given a set of stacking weights", "topics": [ "BPS_postdraws_MvT" ] }, { "page": "BPS_pred_MvT", "title": "Compute the BPS spatial prediction given a set of stacking weights", "topics": [ "BPS_pred_MvT" ] }, { "page": "BPS_PseudoBMA", "title": "Combine subset models wiht Pseudo-BMA", "topics": [ "BPS_PseudoBMA" ] }, { "page": "BPS_weights_MvT", "title": "Compute the BPS weights by convex optimization", "topics": [ "BPS_weights_MvT" ] }, { "page": "conv_opt", "title": "Solver for Bayesian Predictive Stacking of Predictive densities convex optimization problem", "topics": [ "conv_opt" ] }, { "page": "CVXR_opt", "title": "Compute the BPS weights by convex optimization", "topics": [ "CVXR_opt" ] }, { "page": "d_pred_cpp_MvT", "title": "Evaluate the density of a set of unobserved response with respect to the conditional posterior predictive", "topics": [ "d_pred_cpp_MvT" ] }, { "page": "dens_kcv_MvT", "title": "Compute the KCV of the density evaluations for fixed values of the hyperparameters", "topics": [ "dens_kcv_MvT" ] }, { "page": "dens_loocv_MvT", "title": "Compute the LOOCV of the density evaluations for fixed values of the hyperparameters", "topics": [ "dens_loocv_MvT" ] }, { "page": "expand_grid_cpp", "title": "Build a grid from two vector (i.e. equivalent to 'expand.grid()' in 'R')", "topics": [ "expand_grid_cpp" ] }, { "page": "fit_cpp_MvT", "title": "Compute the parameters for the posteriors distribution of beta and Sigma (i.e. updated parameters)", "topics": [ "fit_cpp_MvT" ] }, { "page": "forceSymmetry_cpp", "title": "Function to subset data for meta-analysis", "topics": [ "forceSymmetry_cpp" ] }, { "page": "models_dens_MvT", "title": "Return the CV predictive density evaluations for all the model combinations", "topics": [ "models_dens_MvT" ] }, { "page": "post_draws_MvT", "title": "Sample R draws from the posterior distributions", "topics": [ "post_draws_MvT" ] }, { "page": "pred_bayesMvLMconjugate", "title": "Predictive sampler for Conjugate Bayesian Multivariate Linear Models", "topics": [ "pred_bayesMvLMconjugate" ] }, { "page": "predict.spBPS", "title": "Predict at new locations using a fitted spBPS model", "topics": [ "predict.spBPS" ] }, { "page": "r_pred_cond_MvT", "title": "Draw from the conditional posterior predictive for a set of unobserved covariates", "topics": [ "r_pred_cond_MvT" ] }, { "page": "r_pred_joint_MvT", "title": "Draw from the joint posterior predictive for a set of unobserved covariates", "topics": [ "r_pred_joint_MvT" ] }, { "page": "r_pred_marg_MvT", "title": "Draw from the joint posterior predictive for a set of unobserved covariates", "topics": [ "r_pred_marg_MvT" ] }, { "page": "sample_index", "title": "Function to sample integers (index)", "topics": [ "sample_index" ] }, { "page": "spBPS", "title": "Unified spatial BPS workflow (multivariate path, works for q = 1)", "topics": [ "spBPS" ] }, { "page": "spBPS_old", "title": "Unified spatial BPS workflow (multivariate path, works for q = 1)", "topics": [ "spBPS_old" ] }, { "page": "subset_data", "title": "Function to subset data for meta-analysis", "topics": [ "subset_data" ] } ], "_pkglogo": "https://github.com/lucapresicce/spbps/raw/HEAD/man/figures/logo.png", "_readme": "https://github.com/lucapresicce/spbps/raw/HEAD/README.md", "_rundeps": [ "backports", "checkmate", "clarabel", "cli", "CVXR", "gmp", "highs", "lattice", "Matrix", "mniw", "osqp", "Rcpp", "RcppArmadillo", "RcppEigen", "S7", "scs", "slam" ], "_sysdeps": [ { "shlib": "liblapack", "package": "libopenblas0-pthread", "source": "openblas", "version": "0.3.32+ds-5", "name": "openblas", "homepage": "https://www.openblas.net/", "description": "Optimized BLAS (linear algebra) library (shared lib, pthread)" }, { "shlib": "libblas", "package": "libopenblas0-pthread", "source": "openblas", "version": "0.3.32+ds-5", "name": "openblas", "homepage": "https://www.openblas.net/", "description": "Optimized BLAS (linear algebra) library (shared lib, pthread)" }, { "shlib": "libstdc++", "package": "libstdc++6", "source": "gcc", "version": "16-20260322-1ubuntu1", "name": "c++", "homepage": "http://gcc.gnu.org/", "description": "GNU Standard C++ Library v3" }, { "shlib": "libgomp", "package": "libgomp1", "source": "gcc", "version": "16-20260322-1ubuntu1", "name": "openmp", "homepage": "http://gcc.gnu.org/", "description": "GCC OpenMP (GOMP) support library" } ], "_vignettes": [ { "source": "tutorial.Rmd", "filename": "tutorial.html", "title": "Double Bayesian Predictive Stacking for Spatial Analysis - Tutotial", "engine": "knitr::rmarkdown", "headings": [ "Working packages", "Data generation", "Setting priors and hyperparameters", "Setting dimensions", "Double BPS parallel fit", "Results collection", "Plot results" ], "created": "2024-10-18 10:29:39", "modified": "2026-05-07 16:24:47", "commits": 6 } ], "_score": 4.931966114728173, "_indexed": true, "_nocasepkg": "spbps", "_universes": [ "lucapresicce" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "2.0-1", "date": "2026-10-06T12:55:35.000Z", "distro": "resolute", "arch": "aarch64", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/6c3bffa9b271dd246c9c0d7c783a3c6e2bf4673eb902cce6923111ff02fb4efd", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" }, { "r": "4.7.0", "os": "linux", "version": "2.0-1", "date": "2026-10-06T12:55:39.000Z", "distro": "resolute", "arch": "x86_64", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/e08bfce8a737fab4f9daaae3cff16d3c3860037fd325b46c0840bb68e1e4b86f", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" }, { "r": "4.6.1", "os": "linux", "version": "2.0-1", "date": "2026-10-06T12:55:26.000Z", "distro": "resolute", "arch": "aarch64", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/eb60103018f4385caef6c930664b404770534df1d5eb0d05de84d9fe70139de0", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" }, { "r": "4.6.1", "os": "linux", "version": "2.0-1", "date": "2026-10-06T12:55:59.000Z", "distro": "resolute", "arch": "x86_64", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/a46eb7875f071cad1d49abf7887c6488752abbc7e06f6d51f8213f419f41a9ba", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" }, { "r": "4.5.3", "os": "mac", "version": "2.0-1", "date": "2026-10-06T12:56:08.000Z", "arch": "aarch64", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/d11803b2d55ec402b8699c6fe4cf3b22587eae07729ea85ca1ff863a5e34099f", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" }, { "r": "4.5.3", "os": "mac", "version": "2.0-1", "date": "2026-10-06T12:57:59.000Z", "arch": "x86_64", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/6ff83ad8fec7da776f3ff4ae2c35e1e93bd22c23bddeb84920f2905968daf599", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" }, { "r": "4.6.1", "os": "mac", "version": "2.0-1", "date": "2026-10-06T12:55:43.000Z", "arch": "aarch64", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/51cecb6b60383e79ab48890882907f3c0d1dffa1d774ec4afafd21998a98cad7", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" }, { "r": "4.6.1", "os": "mac", "version": "2.0-1", "date": "2026-10-06T12:58:06.000Z", "arch": "x86_64", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/ea0eba04de9e2cb1d0c8e22e5da59c2e2bbd23db7a85337bc268872bf8376620", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" }, { "r": "4.6.0", "os": "wasm", "version": "2.0-1", "date": "2026-10-06T12:55:57.000Z", "arch": "emscripten", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/32b2cfaba3bfa96ec5497caabebc788b03f16d66c400b987ac5356260c2adc76", "status": "success", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" }, { "r": "4.7.0", "os": "win", "version": "2.0-1", "date": "2026-10-06T12:58:46.000Z", "arch": "aarch64", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/4259bd2afe09da5ea5d628033da93366e265ae00629cd386fc419f2367ab076a", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" }, { "r": "4.7.0", "os": "win", "version": "2.0-1", "date": "2026-10-06T12:54:42.000Z", "arch": "x86_64", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/3ddd6a3b3a23cc065e0175a840a2ff9944bf703e1cc5524dfdd7cb64a5426052", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" }, { "r": "4.5.3", "os": "win", "version": "2.0-1", "date": "2026-10-06T12:54:52.000Z", "arch": "x86_64", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/e81ff09d235187202f7049f63fcfef6d360582065737fd037663b1a21c0d37c0", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" }, { "r": "4.6.1", "os": "win", "version": "2.0-1", "date": "2026-10-06T12:58:31.000Z", "arch": "aarch64", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/71acd9b607e6229acd6f497f7a245f10af052f8fb95ad2666cd211524e5a24c7", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" }, { "r": "4.6.1", "os": "win", "version": "2.0-1", "date": "2026-10-06T12:55:03.000Z", "arch": "x86_64", "commit": "7881eacb2894b4e203386e7e13a584429683d5a1", "fileid": "https://r2.ropensci.org/fb22ebec87bdb2495361654d96faac3c31b9b4c427acde81885e017c355ec37c", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/lucapresicce/actions/runs/37465950596" } ] }