Automated multi-path General-to-Specific (GETS) modelling of the mean and variance of a regression, and indicator saturation methods for detecting and testing for structural breaks in the mean.

SPRE Statistics for Exploring Heterogeneity in Meta-Analysis
An implementation of SPRE (standardised predicted random-effects)
statistics in R to explore heterogeneity in genetic association meta-
analyses, as described by Magosi et al. (2019)
<doi:10.1093/bioinformatics/btz590>. SPRE statistics are precision
weighted residuals that indicate the direction and extent with which
individual study-effects in a meta-analysis deviate from the average
genetic effect. Overly influential positive outliers have the potential
to inflate average genetic effects in a meta-analysis whilst negative
outliers might lower or change the direction of effect. See the 'getspres'
website for documentation and examples
<https://magosil86.github.io/getspres/>.

knitr (>= 1.10.5), testthat, covr, rmarkdown

Getting to the Bottom, A Package for Learning Optimization
Methods
Getting to the Bottom is a companion package for the "Getting to
the Bottom" optimization methods series at Statisticisviews.com.  The
package contains data and code to reproduce the examples in the articles.

Getting to the Bottom is a companion package for the "Getting to
the Bottom" optimization methods series at Statisticsviews.com.  The
package contains data and code to reproduce the examples in the articles.

R (>= 3.0.2), ggplot2, grid, Matrix, lpSolve, reshape2

Learning Optimization and Machine Learning for Statistics
Getting to the Bottom accompanies the "Getting to
the Bottom" optimization methods series at Statisticsviews.com.  It
contains data and code to reproduce the examples in the articles.

A function to retrieve the system timezone on Unix systems
which has been found to find an answer when 'Sys.timezone()' has failed.
It is based on an answer by Duane McCully posted on 'StackOverflow', and
adapted to be callable from R.

A function to retrieve the system timezone on Unix systems
which has been found to find an answer when 'Sys.timezone()' has failed.
It is based on an answer by Duane McCully posted on 'StackOverflow', and
adapted to be callable from R. The package also builds on Windows, but
just returns NULL.