Open Trade Statistics API Wrapper and Utility Program

Access 'Open Trade Statistics' API from R to download international trade data.

Read and Write C3D Motion Capture Files

A wrapper for the 'EZC3D' library to work with C3D motion capture data.

Spatial Parallel Computing by Hierarchical Data Partitioning

Geospatial data computation is parallelized by grid, hierarchy, or raster files. Based on 'future' (Bengtsson, 2024 ) and 'mirai' (Gao et al., 2025 ) parallel back-ends, 'terra' (Hijmans et al., 2025 ) and 'sf' (Pebesma et al., 2024 ) functions as well as convenience functions in the package can be distributed over multiple threads. The simplest way of parallelizing generic geospatial computation is to start from par_pad_*() functions to par_grid(), par_hierarchy(), or par_multirasters() functions. Virtually any functions accepting classes in 'terra' or 'sf' packages can be used in the three parallelization functions. A common raster-vector overlay operation is provided as a function extract_at(), which uses 'exactextractr' (Baston, 2023 ), with options for kernel weights for summarizing raster values at vector geometries. Other convenience functions for vector-vector operations including simple areal interpolation (summarize_aw()) and summation of exponentially decaying weights (summarize_sedc()) are also provided.

Edit and Validate Darwin Core Taxon Data

Edit and validate taxonomic data in compliance with Darwin Core standards (Darwin Core 'Taxon' class < https://dwc.tdwg.org/terms/#taxon>).

Ergonomic Methods for Assessing Spatial Models

Assessing predictive models of spatial data can be challenging, both because these models are typically built for extrapolating outside the original region represented by training data and due to potential spatially structured errors, with "hot spots" of higher than expected error clustered geographically due to spatial structure in the underlying data. Methods are provided for assessing models fit to spatial data, including approaches for measuring the spatial structure of model errors, assessing model predictions at multiple spatial scales, and evaluating where predictions can be made safely. Methods are particularly useful for models fit using the 'tidymodels' framework. Methods include Moran's I ('Moran' (1950) ), Geary's C ('Geary' (1954) ), Getis-Ord's G ('Ord' and 'Getis' (1995) ), agreement coefficients from 'Ji' and Gallo (2006) (), agreement metrics from 'Willmott' (1981) () and 'Willmott' 'et' 'al'. (2012) (), an implementation of the area of applicability methodology from 'Meyer' and 'Pebesma' (2021) (), and an implementation of multi-scale assessment as described in 'Riemann' 'et' 'al'. (2010) ().

Find Free Versions of Scholarly Publications via Unpaywall

This web client interfaces Unpaywall < https://unpaywall.org/products/api>, formerly oaDOI, a service finding free full-texts of academic papers by linking DOIs with open access journals and repositories. It provides unified access to various data sources for open access full-text links including Crossref and the Directory of Open Access Journals (DOAJ). API usage is free and no registration is required.

Interactive, Complex Heatmaps

Make complex, interactive heatmaps. 'iheatmapr' includes a modular system for iteratively building up complex heatmaps, as well as the iheatmap() function for making relatively standard heatmaps.

Call Google's 'Natural Language', 'Cloud Translation', 'Cloud Speech', and 'Cloud Text-to-Speech' APIs

Access Google Cloud machine learning APIs for text and speech tasks. Use the Cloud Translation API for text detection and translation, the Natural Language API to analyze sentiment, entities, and syntax, the Cloud Speech API to transcribe audio to text, and the Cloud Text-to-Speech API to synthesize text into audio files.

Base de Datos de Facil Acceso del Censo 2017 de Chile (2017 Chilean Census Easy Access Database)

Provee un acceso conveniente a mas de 17 millones de registros de la base de datos del Censo 2017. Los datos fueron importados desde el DVD oficial del INE usando el Convertidor REDATAM creado por Pablo De Grande. Esta paquete esta documentado intencionalmente en castellano asciificado para que funcione sin problema en diferentes plataformas. (Provides convenient access to more than 17 million records from the Chilean Census 2017 database. The datasets were imported from the official DVD provided by the Chilean National Bureau of Statistics by using the REDATAM converter created by Pablo De Grande and in addition it includes the maps accompanying these datasets.)

High-Dimensional Cure Models

Provides functions for fitting various penalized parametric and semi-parametric mixture cure models with different penalty functions, testing for a significant cure fraction, and testing for sufficient follow-up as described in Fu et al (2022) and Archer et al (2024). False discovery rate controlled variable selection is provided using model-X knock-offs.