Package: flagr 0.3.2
flagr: Implementation of Flag Aggregation
Three methods are implemented in R to facilitate the aggregations of flags in official statistics. From the underlying flags the highest in the hierarchy, the most frequent, or with the highest total weight is propagated to the flag(s) for EU or other aggregates. Below there are some reference documents for the topic: <https://sdmx.org/wp-content/uploads/CL_OBS_STATUS_v2_1.docx>, <https://sdmx.org/wp-content/uploads/CL_CONF_STATUS_1_2_2018.docx>, <http://ec.europa.eu/eurostat/data/database/information>, <http://www.oecd.org/sdd/33869551.pdf>, <https://sdmx.org/wp-content/uploads/CL_OBS_STATUS_implementation_20-10-2014.pdf>.
Authors:
flagr_0.3.2.tar.gz
flagr_0.3.2.zip(r-4.5)flagr_0.3.2.zip(r-4.4)flagr_0.3.2.zip(r-4.3)
flagr_0.3.2.tgz(r-4.4-any)flagr_0.3.2.tgz(r-4.3-any)
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flagr_0.3.2.tgz(r-4.4-emscripten)flagr_0.3.2.tgz(r-4.3-emscripten)
flagr.pdf |flagr.html✨
flagr/json (API)
# Install 'flagr' in R: |
install.packages('flagr', repos = c('https://mmatyi.r-universe.dev', 'https://cloud.r-project.org')) |
- test_data - This data set is a fictive data set with fictive values and flags for testing purposes.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:64c0038b72. Checks:OK: 1 WARNING: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 27 2024 |
R-4.5-win | WARNING | Oct 27 2024 |
R-4.5-linux | WARNING | Oct 27 2024 |
R-4.4-win | WARNING | Oct 27 2024 |
R-4.4-mac | WARNING | Oct 27 2024 |
R-4.3-win | WARNING | Oct 27 2024 |
R-4.3-mac | WARNING | Oct 27 2024 |
Exports:flag_divideflag_frequencyflag_hierarchyflag_weightedpropagate_flag
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Assignment of the weights for the multiple flags | flag_divide |
Flag aggregation by the frequency count method | flag_frequency |
Flag aggregation by the hierarchical inheritance method | flag_hierarchy |
Flag aggregation by the weighted frequency method | flag_weighted |
Derive flags for an aggregates using diffrent methods | propagate_flag |
This data set is a fictive data set with fictive values and flags for testing purposes. | test_data |