Flexible and Customisable Logging System

A comprehensive logging framework for R applications that provides hierarchical logging levels, database integration, and contextual logging capabilities. The package supports 'SQLite' storage for persistent logs, provides colour-coded console output for better readability, includes parallel processing support, and implements structured error reporting with 'JSON' formatting.

A Fully Featured Logging Framework

A flexible, light-weight logging framework based on 'R6' classes. It supports hierarchical loggers, structured logging, output to plaintext, 'JSON', (rotating) files, and memory buffers. Additional appenders for 'Elasticsearch', 'Dynatrace', databases, email and push notifications, and more are available in the 'lgrExtra' package.

Zooarchaeological Analysis with Log-Ratios

Includes functions and reference data to generate and manipulate log-ratios (also known as log size index (LSI) values) from measurements obtained on zooarchaeological material. Log ratios are used to compare the relative (rather than the absolute) dimensions of animals from archaeological contexts (Meadow 1999, ISBN: 9783896463883). zoolog is also able to seamlessly integrate data and references with heterogeneous nomenclature, which is internally managed by a zoolog thesaurus. A preliminary version of the zoolog methods was first used by Trentacoste, Nieto-Espinet, and Valenzuela-Lamas (2018) .

Web Server Log Analysis

Provides Apache and IIS log analytics for transaction performance, client populations and workload definitions.

Log-Likelihood Functions for 'rxode2'

Provides the log-likelihoods with gradients from 'stan' (Carpenter et al (2015), ) needed for generalized log-likelihood estimation in 'nlmixr2' (Fidler et al (2019) ). This is split of to reduce computational burden of recompiling 'rxode2' (Wang, Hallow and James (2016) ) which runs the 'nlmixr2' models during estimation.

log Normal Linear Regression

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) .

Generalised log-Linear Model

Routines for log-linear models of incomplete contingency tables, including some latent class models, via EM and Fisher scoring approaches. Allows bootstrapping. See Espeland and Hui (1987) for general approach.

Log-Gaussian Cox Process

Spatial and spatio-temporal modelling of point patterns using the log-Gaussian Cox process. Bayesian inference for spatial, spatiotemporal, multivariate and aggregated point processes using Markov chain Monte Carlo. See Benjamin M. Taylor, Tilman M. Davies, Barry S. Rowlingson, Peter J. Diggle (2015) .

Log Rotation and Conditional Backups

Conditionally rotate or back-up files based on their size or the date of the last backup; inspired by the 'Linux' utility 'logrotate'.

Distributions for Generalized Additive Models for Location Scale and Shape

A set of distributions which can be used for modelling the response variables in Generalized Additive Models for Location Scale and Shape, Rigby and Stasinopoulos (2005), . The distributions can be continuous, discrete or mixed distributions. Extra distributions can be created, by transforming, any continuous distribution defined on the real line, to a distribution defined on ranges 0 to infinity or 0 to 1, by using a 'log' or a 'logit' transformation respectively.