Package: representr 0.1.5

Andee Kaplan

representr: Create Representative Records After Entity Resolution

An implementation of Kaplan, Betancourt, Steorts (2022) <doi:10.1080/00031305.2022.2041482> that creates representative records for use in downstream tasks after entity resolution is performed. Multiple methods for creating the representative records (data sets) are provided.

Authors:Andee Kaplan [aut, cre], Brenda Betancourt [aut], Rebecca C. Steorts [aut]

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representr/json (API)
NEWS

# Install 'representr' in R:

install.packages('representr', repos = c('https://cleanzr.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cleanzr/representr/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

identity.rl_reg1 - 500 records suitable for record linkage with additional regression variables
identity.rl_reg2 - 500 records suitable for record linkage with additional regression variables
identity.rl_reg5 - 500 records suitable for record linkage with additional regression variables
linkage.rl - 500 records suitable for record linkage with additional regression variables
rl_reg1 - 500 records suitable for record linkage with additional regression variables
rl_reg2 - 500 records suitable for record linkage with additional regression variables
rl_reg5 - 500 records suitable for record linkage with additional regression variables

On CRAN:

downstream-tasks post-linkage-analysis record-linkage

4.68 score 8 stars 12 scripts 178 downloads 10 exports 21 dependencies

Last updated 1 years agofrom:4e6534a7c3. Checks:OK: 9. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 06 2024
R-4.5-win-x86_64	OK	Nov 06 2024
R-4.5-linux-x86_64	OK	Nov 06 2024
R-4.4-win-x86_64	OK	Nov 06 2024
R-4.4-mac-x86_64	OK	Nov 06 2024
R-4.4-mac-aarch64	OK	Nov 06 2024
R-4.3-win-x86_64	OK	Nov 06 2024
R-4.3-mac-x86_64	OK	Nov 06 2024
R-4.3-mac-aarch64	OK	Nov 06 2024

Exports:clust_composite clust_proto_minimax clust_proto_random dist_binary dist_col_type dist_col_type_slow emp_kl_div pp_weights represent within_category_compare_cpp

Dependencies:cli codetools doParallel dplyr fansi foreach generics glue iterators lifecycle magrittr pillar pkgconfig R6 Rcpp rlang tibble tidyselect utf8 vctrs withr

Prototyping with representr

Andee Kaplan and Rebecca C. Steorts

Rendered fromrepresentr.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2021-07-27
Started: 2018-10-01

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Composite record from a cluster using a weighted average of each column values.	clust_composite
Prototype record from a cluster.	clust_proto_minimax clust_proto_random maxmin_compare random_compare within_category_compare
The distance between two records	dist_binary dist_col_type_slow
dist_col_type Inner column type record distance function	dist_col_type
Calculate the empirical KL divergence for a representative dataset as compared to the true dataset	emp_kl_div
Get posterior weights for each record post record-linkage using posterior prototyping.	pp_weights
Create a representative dataset post record-linkage.	represent
representr: A package for creating representative records post-record linkage.	representr
500 records suitable for record linkage with additional regression variables	identity.rl_reg1 identity.rl_reg2 identity.rl_reg5 linkage.rl rl_reg1 rl_reg2 rl_reg5
within_category_compare_cpp Inner column type record distance function	within_category_compare_cpp