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'.

Logging for 'dplyr' and 'tidyr' Functions

Provides feedback about 'dplyr' and 'tidyr' operations.

Vectorised Tools for URL Handling and Parsing

A toolkit for all URL-handling needs, including encoding and decoding, parsing, parameter extraction and modification. All functions are designed to be both fast and entirely vectorised. It is intended to be useful for people dealing with web-related datasets, such as server-side logs, although may be useful for other situations involving large sets of URLs.

A Lightweight, Modern and Flexible Logging Utility

Inspired by the the 'futile.logger' R package and 'logging' Python module, this utility provides a flexible and extensible way of formatting and delivering log messages with low overhead.

Log-Analytic Methods for Multiplicative Effects

Log-analytic methods intended for testing multiplicative effects.

Weighted Tidy Log Odds Ratio

How can we measure how the usage or frequency of some feature, such as words, differs across some group or set, such as documents? One option is to use the log odds ratio, but the log odds ratio alone does not account for sampling variability; we haven't counted every feature the same number of times so how do we know which differences are meaningful? Enter the weighted log odds, which 'tidylo' provides an implementation for, using tidy data principles. In particular, here we use the method outlined in Monroe, Colaresi, and Quinn (2008) to weight the log odds ratio by a prior. By default, the prior is estimated from the data itself, an empirical Bayes approach, but an uninformative prior is also available.

One-Sample Log-Rank Test

The log-rank test is performed to assess the survival outcomes between two group. When there is no proper control group or obtaining such data is cumbersome, one sample log-rank test can be applied. This package performs one sample log-rank test as described in Finkelstein et al. (2003) and variation of the test for small sample sizes which is detailed in FD Liddell (1984) paper. Visualization function in the package generates Kaplan-Meier Curve comparing survival curve of the general population against that of the population of interest.