survey (>= 3.34), boot, ellipse, parallel, knitr, rmarkdown

Functions to fit log-multiplicative models using 'gnm', with
support for convenient printing, plots, and jackknife/bootstrap
standard errors. For complex survey data, models can be fitted from
design objects from the 'survey' package. Currently supported models
include UNIDIFF (Erikson & Goldthorpe, 1992),
a.k.a. log-multiplicative layer effect model (Xie, 1992)
<doi:10.2307/2096242>, and several association models:
Goodman (1979) <doi:10.2307/2286971>
row-column association models of the RC(M) and RC(M)-L families
with one or several dimensions; two skew-symmetric association
models proposed by Yamaguchi (1990) <doi:10.2307/271086>
and by van der Heijden & Mooijaart (1995) <doi:10.1177/0049124195024001002>
Functions allow computing the intrinsic association coefficient
(see Bouchet-Valat (2022) <doi:10.1177/0049124119852389>)
and the Altham (1970) index <doi:10.1111/j.2517-6161.1970.tb00816.x>,
including via the Bayes shrinkage estimator proposed
by Zhou (2015) <doi:10.1177/0081175015570097>;
and the RAS/IPF/Deming-Stephan algorithm.

Functions for the Lognormal Distribution
The lognormal distribution
(Limpert et al. (2001) <doi:10.1641/0006-3568(2001)051%5B0341:lndats%5D2.0.co;2>)
can characterize uncertainty that is bounded by zero.
This package provides estimation of distribution parameters, computation of
moments and other basic statistics, and an approximation of the distribution
of the sum of several correlated lognormally distributed variables
(Lo 2013 <doi:10.12988/ams.2013.39511>) and the approximation of the
difference of two correlated lognormally distributed variables
(Lo 2012 <doi:10.1155/2012/838397>).
markdown, rmarkdown, testthat, knitr, dplyr, ggplot2,
mvtnorm, purrr, tidyr

The lognormal distribution
(Limpert al. (2001) <doi:10.1641/0006-3568(2001)051[0341:lndats]2.0.co;2>)
can characterize uncertainty that is bounded by zero.
This package provides estimation of distribution parameters, computation of
moments and other basic statistics, and an approximation of the distribution
of the sum of several correlated lognormally distributed variables
(Lo 2013 <doi:10.12988/ams.2013.39511>).
testthat, knitr, dplyr, ggplot2, mvtnorm, purrr, tidyr