Various R Programming Tools

Functions to assist in R programming, including: - assist in developing, updating, and maintaining R and R packages ('ask', 'checkRVersion', 'getDependencies', 'keywords', 'scat'), - calculate the logit and inverse logit transformations ('logit', 'inv.logit'), - test if a value is missing, empty or contains only NA and NULL values ('invalid'), - manipulate R's .Last function ('addLast'), - define macros ('defmacro'), - detect odd and even integers ('odd', 'even'), - convert strings containing non-ASCII characters (like single quotes) to plain ASCII ('ASCIIfy'), - perform a binary search ('binsearch'), - sort strings containing both numeric and character components ('mixedsort'), - create a factor variable from the quantiles of a continuous variable ('quantcut'), - enumerate permutations and combinations ('combinations', 'permutation'), - calculate and convert between fold-change and log-ratio ('foldchange', 'logratio2foldchange', 'foldchange2logratio'), - calculate probabilities and generate random numbers from Dirichlet distributions ('rdirichlet', 'ddirichlet'), - apply a function over adjacent subsets of a vector ('running'), - modify the TCP_NODELAY ('de-Nagle') flag for socket objects, - efficient 'rbind' of data frames, even if the column names don't match ('smartbind'), - generate significance stars from p-values ('stars.pval'), - convert characters to/from ASCII codes ('asc', 'chr'), - convert character vector to ASCII representation ('ASCIIfy'), - apply title capitalization rules to a character vector ('capwords').

Record Events and Issues

Logger to keep track of informational events and errors useful for debugging.

Lightweight Logging for R Scripts

Provides flexible but lightweight logging facilities for R scripts. Supports priority levels for logs and messages, flagging messages, capturing script output, switching logs, and logging to files or connections.

Modern Logging for the R Ecosystem

An effortless 'ndjson' (newline-delimited 'JSON') logger, with two primary log-writing interfaces. It provides a set of wrappings for base R's message(), warning(), and stop() functions that maintain identical functionality, but also log the handler message to an 'ndjson' log file. 'loggit' also exports its internal 'loggit()' function for powerful and configurable custom logging. No change in existing code is necessary to use this package, and should only require additions to fully leverage the power of the logging system. 'loggit' also provides a log reader for reading an 'ndjson' log file into a data frame, log rotation, and live echo of the 'ndjson' log messages to terminal 'stdout' for log capture by external systems (like containers). 'loggit' is ideal for Shiny apps, data pipelines, modeling work flows, and more. Please see the vignettes for detailed example use cases.

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.

Web Server Log Analysis

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

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) .

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.