The R Journal: article published in 2018, volume 10:1

lba: An R Package for Latent Budget Analysis
Enio G. Jelihovschi and Ivan Bezerra Allaman , The R Journal (2018) 10:1, pages 269-287.

Abstract The latent budget model is a mixture model for compositional data sets in which the entries, a contingency table, may be either realizations from a product multinomial distribution or distribution free. Based on this model, the latent budget analysis considers the interactions of two variables; the ex planatory (row) and the response (column) variables. The package lba uses expectation-maximization and active constraints method (ACM) to carry out, respectively, the maximum likelihood and the least squares estimation of the model parameters. It contains three main functions, lba which performs the analysis, goodnessfit for model selection and goodness of fit and the plotting functions plotcorr and plotlba used as a help in the interpretation of the results.

Received: 2017-07-12; online 2018-05-21, supplementary material, (1.1 KiB)
CRAN packages: lba, alabama, plotrix, scatterplot3d, rgl, MASS
CRAN Task Views implied by cited CRAN packages: Graphics, Multivariate, Psychometrics, Distributions, Econometrics, Environmetrics, NumericalMathematics, Optimization, Robust, SocialSciences, SpatioTemporal

This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2018-026,
  author = {Enio G. Jelihovschi and Ivan Bezerra Allaman},
  title = {{lba: An R Package for Latent Budget Analysis}},
  year = {2018},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2018-026},
  url = {https://doi.org/10.32614/RJ-2018-026},
  pages = {269--287},
  volume = {10},
  number = {1}
}