SUMMER: Small-Area-Estimation Unit/Area Models and Methods for Estimation in R

Provides methods for spatial and spatio-temporal smoothing of demographic and health indicators using survey data, with particular focus on estimating and projecting under-five mortality rates, described in Mercer et al. (2015) <doi:10.1214/15-AOAS872>, Li et al. (2019) <doi:10.1371/journal.pone.0210645>, Wu et al. (DHS Spatial Analysis Reports No. 21, 2021), and Li et al. (2023) <doi:10.48550/arXiv.2007.05117>.

Version: 1.4.0
Depends: R (≥ 3.5)
Imports: survey, stats, spdep, survival, ggplot2, scales, utils, Matrix, reshape2, viridis, sp, sf, shadowtext, ggridges, methods, data.table, RColorBrewer, grDevices, fields, terra, haven
Suggests: INLA, knitr, rmarkdown, readstata13, patchwork, rdhs, R.rsp, sae, dplyr, tidyr, raster
Published: 2024-03-01
Author: Zehang R Li [cre, aut], Bryan D Martin [aut], Yuan Hsiao [aut], Jessica Godwin [aut], John Paige [aut], Peter Gao [aut], Jon Wakefield [aut], Samuel J Clark [aut], Geir-Arne Fuglstad [aut], Andrea Riebler [aut]
Maintainer: Zehang R Li <lizehang at gmail.com>
BugReports: https://github.com/richardli/SUMMER/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/richardli/SUMMER, https://richardli.github.io/SUMMER/
NeedsCompilation: no
Additional_repositories: https://inla.r-inla-download.org/R/testing/
Materials: README NEWS
In views: OfficialStatistics
CRAN checks: SUMMER results

Documentation:

Reference manual: SUMMER.pdf
Vignettes: Generic small area estimation
Case Study: Estimating Subnational U5MR using DHS data
Estimating Subnational U5MR using Simulated Data

Downloads:

Package source: SUMMER_1.4.0.tar.gz
Windows binaries: r-devel: SUMMER_1.4.0.zip, r-release: SUMMER_1.4.0.zip, r-oldrel: SUMMER_1.4.0.zip
macOS binaries: r-release (arm64): SUMMER_1.4.0.tgz, r-oldrel (arm64): SUMMER_1.4.0.tgz, r-release (x86_64): SUMMER_1.4.0.tgz
Old sources: SUMMER archive

Reverse dependencies:

Reverse imports: GeoAdjust, surveyPrev
Reverse suggests: survey

Linking:

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