Title: A Simple Logging System for R, Based on 'log4j'
person("Kirill", "Müller", email = "krlmlr+r@mailbox.org",
person("Aaron", "Jacobs", email = "atheriel@gmail.com",
Description: The log4r package is meant to provide a fast, lightweight,
object-oriented approach to logging in R based on the widely-emulated

Suggests: futile.logger, knitr, lgr, logger, logging, microbenchmark,

Title: A Fast and Lightweight Logging System for R, Based on 'log4j'

Suggests: futile.logger, httr, jsonlite, knitr, lgr, logger, logging,
loggit, microbenchmark, rlog, rmarkdown, rsyslog, testthat

Title: Computing Log-Transformed Kernel Density Estimates for Positive
Author: Hien D. Nguyen, Andrew T. Jones, and Geoffrey J. McLachlan
Description: 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) <arXiv:1804.08365>.
Packaged: 2018-04-25 08:16:21 UTC; andrewjones

Packaged: 2018-07-23 11:24:30 UTC; andrewjones

Packaged: 2018-07-24 08:02:29 UTC; andrewjones

Description: 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>.
Packaged: 2018-08-09 07:02:52 UTC; andrewjones

Authors@R: c(person(given = c("Vito","M.","R."), family = "Muggeo", role =
Maintainer: Vito M. R. Muggeo <vito.muggeo@unipa.it>
Description: Functions to fits simple linear regression models with log normal errors
and identity link (taking the responses on the original scale). See
Author: Vito M. R. Muggeo [aut, cre] (<https://orcid.org/0000-0002-3386-4054>)

and identity link, i.e. taking the responses on the original scale. See

Title: Natural Logarithms of the Gamma Function for Large Values
Description: Uses approximations to compute the natural logarithm of the Gamma

Title: Relative Risk Regression Using the Log Binomial Model
Description: Methods for fitting log-link GLMs and GAMs for binomial data.
The package uses EM-type algorithms with more stable convergence properties than standard methods.
Packaged: 2014-10-16 03:19:53 UTC; mdonoghoe