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ipfr
View on CRAN: Click
here
Download and install ipfr package within the R console
Install from CRAN:
install.packages("ipfr")
Install from Github:
library("remotes")
install_github("cran/ipfr")
Install by package version:
library("remotes")
install_version("ipfr", "1.0.2")
Attach the package and use:
library("ipfr")
Maintained by
Kyle Ward
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-21
Latest Update: 2020-04-01
Description:
Performs iterative proportional updating given a seed table and
an arbitrary number of marginal distributions. This is commonly used in
population synthesis, survey raking, matrix rebalancing, and other
applications. For example, a household survey may be weighted to match the
known distribution of households by size from the census. An origin/
destination trip matrix might be balanced to match traffic counts.
The approach used by this package is based on a paper from
Arizona State University (Ye, Xin, et. al. (2009)
).
Some enhancements have been made to their work including primary and
secondary target balance/importance, general marginal agreement, and weight
restriction.
How to cite:
Kyle Ward (2019). ipfr: List Balancing for Reweighting and Population Synthesis. R package version 1.0.2, https://cran.r-project.org/web/packages/ipfr
Other packages that cited ipfr R package
View ipfr citation profile
Other R packages that ipfr depends,
imports, suggests or enhances
Functions, R codes and Examples using
the ipfr R package
Some associated functions: adjust_factor . balance_secondary_targets . check_geo_fields . check_missing_categories . check_tables . compare_results . create_target_priority . ipf . ipfr . ipu . ipu_matrix . ipu_nr . process_seed_table . scale_targets . setup_arizona . synthesize .
Some associated R codes: globals.R . ipf.R . ipfr.R . ipu.R . ipu_nr.R . synthesize.R . utils.R . Full ipfr package functions and examples
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