Exactly Rounded Sums, Means and Dot Products

Sums of double-precision numbers computed exactly and rounded once, so the result is the correctly rounded true sum and does not depend on the order of the elements, the platform, or whether R was built with long doubles. Built on the small and large superaccumulators of Neal (2015) . Provides exactly rounded sums, means, cumulative sums, dot products and norms, row, column and grouped sums, accumulators that can be built in pieces and merged across processes, and a registered 'C' interface for other packages.

Parse and Emit 'YAML' 1.2

Converts between 'YAML' 1.2 (< https://yaml.org/spec/1.2.2/>) and ordinary R objects using a bundled copy of the 'cyaml' C11 parser and emitter (< https://github.com/andrewmd5/cyaml>), so there is no system dependency and no runtime dependency beyond R itself. Ambiguous 'YAML' features are handled strictly and predictably: duplicate keys are refused by default, the 'YAML' 1.2 core schema is followed so that yes and no resolve as strings, and integers beyond double precision are preserved rather than silently rounded. A stream of documents and a sequence are different things, and the interface keeps them apart. Input size, nesting depth and the number of values materialised are all bounded, which makes the parser usable on untrusted input.

Curated Agentic Harnesses for R Professional Roles

A bootstrapper that launches a command-line coding agent of the user's choice in a terminal tab pre-configured for a professional R role. Each role is described by a curated harness: a subset of community skills, a system prompt, a folder layout, and quality gates. The package does not run an agent loop and does not call a language model; it discovers the chosen coder binary, generates its configuration, links the curated skills, and opens the terminal. Code written by the agent is run manually by the user, by design, so that every generated script passes through a human audit gate before execution.

Calculate Forest Dynamics

Determines the dynamics of tree species communities (mortality rates, recruitment, loss and gain in basal area, net changes and turnover). Important notes are a) The 'forest_df' argument (data) must contain the columns 'plot' (plot identification), 'spp' (species identification), DBH_1 (Diameter at breast height in first year of measure) and DBH_2 (Diameter at breast height in second year of measure). DBH_1 and DBH_2 must be numeric values; b) example input file in 'data(forest_df_example)'; c) The argument 'inv_time' represents the time between inventories, in years; d) The 'coord' argument must be of the type 'c(longitude, latitude)', with decimal degree values; e) Argument 'add_wd' represents a dataframe with wood density values (g cm-3) format with three columns ('genus', 'species', 'wd'). This argument is set to NULL by default, and if isn't provided, the wood density will be estimated with the getWoodDensity() function from the 'BIOMASS' package.

Microsoft(r)-Inspired Color Palettes

Provide color schemes for maps (and other graphics) based on the color palettes of several Microsoft(r) products. Forked from 'RColorBrewer' v1.1-2.

Add Ipea Editorial Standards to 'ggplot2' Graphics

Convenient functions to create 'ggplot2' graphics following the editorial guidelines of the Institute for Applied Economic Research (Ipea).

Neural Simulation-Based Inference

A native R implementation of neural simulation-based inference, focused on Neural Posterior Estimation. Given a prior over parameters and a simulator, 'neuralsbi' trains a conditional neural density estimator to approximate the Bayesian posterior, enabling amortized, likelihood-free inference. Neural estimators run on the 'torch' back end. It targets applied researchers who want an approachable interface with sensible defaults and built-in posterior diagnostics.

Colombian Macro-Financial Time Series Generator

This repository aims to contribute to the econometric models' production with Colombian data, by providing a set of web-scrapping functions of some of the main macro-financial indicators. All the sources are public and free, but the advantage of these functions is that they directly download and harmonize the information in R's environment. No need to import or download additional files. You only need an internet connection!

'RStudio' Addins for Show Outline of a R Markdown/'LaTeX' Project

'RStudio' allows to show and navigate for the outline of a R Markdown file, but not for R Markdown projects with multiple files. For this reason, I have developed several 'RStudio' addins capable of show project outline. Each addin is specialized in showing projects of different types: R Markdown project, 'bookdown' package project and 'LaTeX' project. There is a configuration file that allows you to customize additional searches.

Calibration of Binary and Multiclass Probabilities

Provides S3 calibrators, metrics, and diagnostics for binary and multiclass probability calibration. Binary methods include Platt scaling, temperature scaling, beta calibration, histogram binning, and isotonic regression. Multiclass methods include temperature scaling, vector scaling, Dirichlet calibration, and a one-vs-rest wrapper for the binary calibrators. A calibration-inference layer adds debiased calibration errors, bootstrap confidence intervals, and a kernel calibration hypothesis test for binary and multiclass predictions, including the strong (canonical) multiclass case. Methods follow Platt (1999, ISBN:9780262194488), Zadrozny and Elkan (2002) , Guo et al. (2017) < https://proceedings.mlr.press/v70/guo17a.html>, Kull et al. (2017) , Kull et al. (2019) , Widmann et al. (2019) , and Kumar et al. (2019) .