Wrappers for Tools in Other Packages for IDE Friendliness

Set of tools aimed at wrapping some of the functionalities of the packages tools, utils and codetools into a nicer format so that an IDE can use them.

Easy Web Scraping

The goal of 'ralger' is to facilitate web scraping in R.

Hidden Smooth Polynomial Regression for Rupture Detection

Several functions that allow by different methods to infer a piecewise polynomial regression model under regularity constraints, namely continuity or differentiability of the link function. The implemented functions are either specific to data with two regimes, or generic for any number of regimes, which can be given by the user or learned by the algorithm. A paper describing all these methods will be submitted soon. The reference will be added to this file as soon as available.

Time Series Analysis Tools

A system contains easy-to-use tools as a support for time series analysis courses. In particular, it incorporates a technique called Generalized Method of Wavelet Moments (GMWM) as well as its robust implementation for fast and robust parameter estimation of time series models which is described, for example, in Guerrier et al. (2013) . More details can also be found in the paper linked to via the URL below.

Airborne LiDAR Filtering Method Based on Multiscale Curvature

Multiscale Curvature Classification of ground returns in 3-D LiDAR point clouds, designed for forested environments. 'RMCC' is a porting to R of the 'MCC-lidar' method by Evans and Hudak (2007) .

Polishing Content for 'Word' and 'PowerPoint'

Set of functions to polish content for Microsoft 'Word' and 'PowerPoint' into 'OOXML'. Polishing is the conversion of the R object into an 'OOXML' representation of the object that can then be added to 'Word' or 'PowerPoint' files.

Shared Memory Multithreading

This project extends 'R' with a mechanism for efficient parallel data access by utilizing 'C++' shared memory. Large data objects can be accessed and manipulated directly from 'R' without redundant copying, providing both speed and memory efficiency. Memshare was published in Thrun, M.C., Märte J.: "Memshare: Memory Sharing for Multicore Computation in R with an Application to Feature Selection by Mutual Information using PDE" (2026), R Journal, .

Specify Reserve Demand Curves

Automatic specification and estimation of reserve demand curves for central bank operations. The package can help to choose the best demand curve and identify additional explanatory variables. Various plot and predict options are included. For more details, see Chen et al. (2023) < https://www.imf.org/en/Publications/WP/Issues/2023/09/01/Modeling-the-Reserve-Demand-to-Facilitate-Central-Bank-Operations-538754>.

'Compressive' Hierarchical Kernel Clustering Toolbox

Routines for efficient cluster analysis of large scale data. This package implements the 'CHICKN' clustering algorithm (see 'Permiakova' 'et' 'al.' (2020) "'CHICKN': Extraction of 'peptide' 'chromatographic' 'elution' profiles from large scale mass 'spectrometry' data by means of 'Wasserstein' 'compressive' hierarchical cluster analysis"). Functions for data compression, hierarchical clustering and post processing are provided.

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