Computes log-transformed kernel density estimates for positive data using a variety of kernels. It follows the methods described in Jones, Nguyen and McLachlan (2018) <doi:10.21105/joss.00870>.

Functions to sample from the double log normal distribution and calculate the density, distribution and quantile functions.

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.

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>).

Functions to fits simple linear regression models with log normal errors 
		and identity link, i.e. taking the responses on the original scale. See
		Muggeo (2018) <doi:10.13140/RG.2.2.18118.16965>.