Package: Spbsampling 1.3.5
Spbsampling: Spatially Balanced Sampling
Selection of spatially balanced samples. In particular, the implemented sampling designs allow to select probability samples well spread over the population of interest, in any dimension and using any distance function (e.g. Euclidean distance, Manhattan distance). For more details, Pantalone F, Benedetti R, and Piersimoni F (2022) <doi:10.18637/jss.v103.c02>, Benedetti R and Piersimoni F (2017) <doi:10.1002/bimj.201600194>, and Benedetti R and Piersimoni F (2017) <arxiv:1710.09116>. The implementation has been done in C++ through the use of 'Rcpp' and 'RcppArmadillo'.
Authors:
Spbsampling_1.3.5.tar.gz
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Spbsampling_1.3.5.tgz(r-4.4-x86_64)Spbsampling_1.3.5.tgz(r-4.4-arm64)Spbsampling_1.3.5.tgz(r-4.3-x86_64)Spbsampling_1.3.5.tgz(r-4.3-arm64)
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Spbsampling.pdf |Spbsampling.html✨
Spbsampling/json (API)
NEWS
| # Install 'Spbsampling' in R: |
| install.packages('Spbsampling', repos = c('https://francescopantalone.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/francescopantalone/spbsampling/issues
- income_emilia - The income of municipalities of "Emilia Romagna".
- lucas_abruzzo - LUCAS data for the region "Abruzzo", Italy.
- simul1 - Simulated Population 1.
- simul2 - Simulated Population 2.
- simul3 - Simulated Population 3.
Last updated 2 years agofrom:8e236a298f. Checks:OK: 1 NOTE: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 19 2024 |
| R-4.5-win-x86_64 | NOTE | Nov 19 2024 |
| R-4.5-linux-x86_64 | NOTE | Nov 19 2024 |
| R-4.4-win-x86_64 | NOTE | Nov 19 2024 |
| R-4.4-mac-x86_64 | NOTE | Nov 19 2024 |
| R-4.4-mac-aarch64 | NOTE | Nov 19 2024 |
| R-4.3-win-x86_64 | NOTE | Nov 19 2024 |
| R-4.3-mac-x86_64 | NOTE | Nov 19 2024 |
| R-4.3-mac-aarch64 | NOTE | Nov 19 2024 |
Exports:hpwdpwdsbistprodstsumswd
Dependencies:RcppRcppArmadillo
