Co-Data Learning for Bayesian Additive Regression Trees

Estimate prior variable weights for Bayesian Additive Regression Trees (BART). These weights correspond to the probabilities of the variables being selected in the splitting rules of the sum-of-trees. Weights are estimated using empirical Bayes and external information on the explanatory variables (co-data). BART models are fitted using the 'dbarts' 'R' package. See Goedhart and others (2023) for details.

ProPublica API Client

Client for accessing data journalism APIs from ProPublica < http://www.propublica.org/>.

Fused Partitioned Regression for Clinical and Omics Data

Fit (generalized) linear regression models in each leaf node of a tree. The tree is constructed using clinical variables only. The linear regression models are constructed using (high-dimensional) omics variables only. The leaf-node-specific regression models are estimated using the penalized likelihood including a standard ridge (L2) penalty and a fusion penalty that links the leaf-node-specific regression models to one another. The intercepts of the leaf nodes reflect the effects of the clinical variables and are left unpenalized. The tree, fitted with the clinical variables only, should be constructed outside of the package with the 'rpart' 'R' package. See Goedhart and others (2024) for details on the method.

'NoSQL' Database Connector

Simplified JSON document database access and manipulation, providing a common API across supported 'NoSQL' databases 'Elasticsearch', 'CouchDB', 'MongoDB' as well as 'SQLite/JSON1', 'PostgreSQL', and 'DuckDB'.

Classes for 'GeoJSON'

Classes for 'GeoJSON' to make working with 'GeoJSON' easier. Includes S3 classes for 'GeoJSON' classes with brief summary output, and a few methods such as extracting and adding bounding boxes, properties, and coordinate reference systems; working with newline delimited 'GeoJSON'; and serializing to/from 'Geobuf' binary 'GeoJSON' format.

A 'HTTP' Server Graphics Device

A graphics device for R that is accessible via network protocols. This package was created to make it easier to embed live R graphics in integrated development environments and other applications. The included 'HTML/JavaScript' client (plot viewer) aims to provide a better overall user experience when dealing with R graphics. The device asynchronously serves graphics via 'HTTP' and 'WebSockets'.

R Interface to the 'Protocol Buffers' 'API' (Version 2 or 3)

Protocol Buffers are a way of encoding structured data in an efficient yet extensible format. Google uses Protocol Buffers for almost all of its internal 'RPC' protocols and file formats. Additional documentation is available in two included vignettes one of which corresponds to our 'JSS' paper (2016, . A sufficiently recent version of 'Protocol Buffers' library is required; currently version 3.3.0 from 2017 is the tested minimum.

Earth Observation Data Cubes from Satellite Image Collections

Processing collections of Earth observation images as on-demand multispectral, multitemporal raster data cubes. Users define cubes by spatiotemporal extent, resolution, and spatial reference system and let 'gdalcubes' automatically apply cropping, reprojection, and resampling using the 'Geospatial Data Abstraction Library' ('GDAL'). Implemented functions on data cubes include reduction over space and time, applying arithmetic expressions on pixel band values, moving window aggregates over time, filtering by space, time, bands, and predicates on pixel values, exporting data cubes as 'netCDF' or 'GeoTIFF' files, plotting, and extraction from spatial and or spatiotemporal features. All computational parts are implemented in C++, linking to the 'GDAL', 'netCDF', 'CURL', and 'SQLite' libraries. See Appel and Pebesma (2019) for further details.

RDF Library Bindings in R

Provides methods to parse, query and serialize information stored in the Resource Description Framework (RDF). RDF is described at < https://www.w3.org/TR/rdf-primer/>. This package supports RDF by implementing an R interface to the Redland RDF C library, described at < https://librdf.org/docs/api/index.html>. In brief, RDF provides a structured graph consisting of Statements composed of Subject, Predicate, and Object Nodes.

Bindings for the 'Geospatial' Data Abstraction Library

Provides bindings to the 'Geospatial' Data Abstraction Library ('GDAL') (>= 1.11.4) and access to projection/transformation operations from the 'PROJ' library. Please note that 'rgdal' will be retired during October 2023, plan transition to sf/stars/'terra' functions using 'GDAL' and 'PROJ' at your earliest convenience (see < https://r-spatial.org/r/2023/05/15/evolution4.html> and earlier blogs for guidance). Use is made of classes defined in the 'sp' package. Raster and vector map data can be imported into R, and raster and vector 'sp' objects exported. The 'GDAL' and 'PROJ' libraries are external to the package, and, when installing the package from source, must be correctly installed first; it is important that 'GDAL' < 3 be matched with 'PROJ' < 6. From 'rgdal' 1.5-8, installed with to 'GDAL' >=3, 'PROJ' >=6 and 'sp' >= 1.4, coordinate reference systems use 'WKT2_2019' strings, not 'PROJ' strings. 'Windows' and 'macOS' binaries (including 'GDAL', 'PROJ' and their dependencies) are provided on 'CRAN'.