Port of Dparser Package (dparser)
A Scannerless GLR parser/parser generator. Note that GLR standing for ‘generalized LR’, where L stands for ‘left-to-right’ and R stands for ‘rightmost (derivation)’. For more information see <https://…/GLR_parser>. This parser is based on the Tomita (1987) algorithm. (Paper can be found at <http://…/J87-1004.pdf> ). The original dparser package documentation can be found at <http://…/>. This allows you to add mini-languages to R (like RxODE’s ODE mini-language Wang, Hallow, and James 2015 <DOI:10.1002/psp4.12052>) or to parse other languages like NONMEM to automatically translate them to R code. To use this in your code, add a LinkingTo ‘dparser’ in your DESCRIPTION file and instead of using ‘#include <dparse.h>’ use ‘#include <dparser.h>’. This also provides a R-based port of the make_dparser <http://…/make_dparser.cat> command called ‘mkdparser’. Additionally you can parse an arbitrary grammar within R using the ‘dparse’ function.

Tools at the Intersection of ‘purrr’ and ‘dplyr’ (purrrlyr)
Some functions at the intersection of ‘dplyr’ and ‘purrr’ that formerly lived in ‘purrr’.

Spatial Data Framework for ggplot2 (ggspatial)
Spatial data plus the power of the ggplot2 framework means easier mapping when input data are already in the form of Spatial* objects.

Intervention in Prediction Measure (IPM) for Random Forests (IPMRF)
Computes IPM for assessing variable importance for random forests. See details at I. Epifanio (2017) <DOI:10.1186/s12859-017-1650-8>.

Automatically Retrieve Multidimensional Distributed Data Sets (startR)
Tool to automatically fetch, transform and arrange subsets of multidimensional data sets (collections of files) stored in local and/or remote file systems or servers, using multicore capabilities where possible. The tool provides an interface to perceive a collection of data sets as a single large multidimensional data array, and enables the user to request for automatic retrieval, processing and arrangement of subsets of the large array. Wrapper functions to add support for custom file formats can be plugged in/out, making the tool suitable for any research field where large multidimensional data sets are involved.

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