Package: mlfit 0.6.1.9028

Amarin Siripanich

mlfit: Iterative Proportional Fitting Algorithms for Nested Structures

The Iterative Proportional Fitting (IPF) algorithm operates on count data. This package offers implementations for several algorithms that extend this to nested structures: 'parent' and 'child' items for both of which constraints can be provided. The fitting algorithms include Iterative Proportional Updating <https://trid.trb.org/view/881554>, Hierarchical IPF <doi:10.3929/ethz-a-006620748>, Entropy Optimization <https://trid.trb.org/view/881144>, and Generalized Raking <doi:10.2307/2290793>. Additionally, a number of replication methods is also provided such as 'Truncate, replicate, sample' <doi:10.1016/j.compenvurbsys.2013.03.004>.

Authors:Kirill Müller [aut, cph], Kay W. Axhausen [ths], Amarin Siripanich [aut, cre], Taha H. Rashidi [ths]

mlfit_0.6.1.9028.tar.gz
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manual.pdf |manual.html✨
card.svg |card.png
mlfit/json (API)

# Install 'mlfit' in R:

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

Bug tracker:https://github.com/mlfit/mlfit/issues

Pkgdown/docs site:https://mlfit.github.io

On CRAN:

5.56 score 14 stars 20 scripts 267 downloads 18 exports 28 dependencies

Last updated from:8b8429b5f9. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	150
source / vignettes	OK	181
linux-release-x86_64	OK	146
macos-release-arm64	OK	89
macos-oldrel-arm64	OK	85
windows-devel	OK	108
windows-release	OK	114
windows-oldrel	OK	124
wasm-release	OK	102

Exports:as_flat_ml_fit_problem compute_margins dss fitting_problem flatten_ml_fit_problem gginv is_ml_fit is_ml_problem margin_to_df ml_fit ml_fit_dss ml_fit_entropy_o ml_fit_hipf ml_fit_ipu ml_problem ml_replicate special_field_names toy_example

Dependencies:BB cachem cli dplyr fastmap forcats generics glue hms kimisc lattice lifecycle magrittr Matrix memoise pillar pkgconfig plyr quadprog R6 Rcpp rlang tibble tidyselect utf8 vctrs withr wrswoR

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
mlfit: Iterative Proportional Fitting Algorithms for Nested Structures	mlfit-package mlfit
Compute margins for a weighting of a multi-level fitting problem	compute_margins margin_to_df
Calibrate sample weights	dss
Return a flattened representation of a multi-level fitting problem instance	as_flat_ml_fit_problem flatten_ml_fit_problem
Generalized Inverse of a Matrix using a custom tolerance or SVD implementation	gginv
Estimate weights for a fitting problem	format.ml_fit is_ml_fit ml_fit ml_fit_dss ml_fit_entropy_o ml_fit_hipf ml_fit_ipu print.ml_fit
Create an instance of a fitting problem	format.ml_problem is_ml_problem ml_problem print.ml_problem special_field_names
Replicate records in a reference sample based on its fitted weights	ml_replicate
Access to toy examples bundled in this package	toy_example