Reads EXIF data using ExifTool <https://exiftool.org> and returns results as a data frame. ExifTool is a platform-independent Perl library plus a command-line application for reading, writing and editing meta information in a wide variety of files. ExifTool supports many different metadata formats including EXIF, GPS, IPTC, XMP, JFIF, GeoTIFF, ICC Profile, Photoshop IRB, FlashPix, AFCP and ID3, as well as the maker notes of many digital cameras by Canon, Casio, FLIR, FujiFilm, GE, HP, JVC/Victor, Kodak, Leaf, Minolta/Konica-Minolta, Motorola, Nikon, Nintendo, Olympus/Epson, Panasonic/Leica, Pentax/Asahi, Phase One, Reconyx, Ricoh, Samsung, Sanyo, Sigma/Foveon and Sony.

Emissions are the mass of pollutants released into the atmosphere. Air quality models need emissions data, with spatial and temporal distribution, to represent air pollutant concentrations. This package, eixport, creates inputs for the air quality models WRF-Chem Grell et al (2005) <doi:10.1016/j.atmosenv.2005.04.027>, MUNICH Kim et al (2018) <doi:10.5194/gmd-11-611-2018> , BRAMS-SPM Freitas et al (2005) <doi:10.1016/j.atmosenv.2005.07.017> and RLINE Snyder et al (2013) <doi:10.1016/j.atmosenv.2013.05.074>. See the eixport website (<https://atmoschem.github.io/eixport/>) for more information, documentations and examples. More details in Ibarra-Espinosa et al (2018) <doi:10.21105/joss.00607>.

Providing easy, portable access to NASA EarthData products through the use of bearer tokens. Much of NASA's public data catalogs hosted and maintained by its 12 Distributed Active Archive Centers ('DAACs') are now made available on the Amazon Web Services S3 storage. However, accessing this data through the standard S3 API is restricted to only to compute resources running inside us-west-2 Data Center in Portland, Oregon, which allows NASA to avoid being charged data egress rates. This package provides public access to the data from any networked device by using the EarthData login application programming interface (API), <https://www.earthdata.nasa.gov/data/earthdata-login>, providing convenient authentication and access to cloud-hosted NASA EarthData products. This makes access to a wide range of earth observation data from any location straight forward and compatible with R packages that are widely used with cloud native earth observation data (such as terra', sf', etc.).

This package provides a flexible framework for calculating Elo ratings and resulting rankings of any two-team-per-matchup system (chess, sports leagues, Go', etc.). This implementation is capable of evaluating a variety of matchups, Elo rating updates, and win probabilities, all based on the basic Elo rating system. It also includes methods to benchmark performance, including logistic regression and Markov chain models.

This package provides tools for calculating evolvability parameters from estimated G-matrices as defined in Hansen and Houle (2008) <doi:10.1111/j.1420-9101.2008.01573.x> and fits phylogenetic comparative models that link the rate of evolution of a trait to the state of another evolving trait (see Hansen et al. 2021 Systematic Biology <doi:10.1093/sysbio/syab079>). The package was released with Bolstad et al. (2014) <doi:10.1098/rstb.2013.0255>, which contains some examples of use.

Given the omnipresence of the assumption of elliptical symmetry, it is essential to be able to test whether that assumption actually holds true or not for the data at hand. This package provides several statistical tests for elliptical symmetry that are described in Babic et al. (2021) <arXiv:2011.12560v2>.

Computes temporal trends in environmental suitability obtained from ecological niche models, based on a set of species presence point coordinates and predictor variables.

Models integrate environmental DNA (eDNA) detection data and traditional survey data to jointly estimate species catch rate (see package vignette: <https://ednajoint.netlify.app/>). Models can be used with count data via traditional survey methods (i.e., trapping, electrofishing, visual) and replicated eDNA detection/nondetection data via polymerase chain reaction (i.e., PCR or qPCR) from multiple survey locations. Estimated parameters include probability of a false positive eDNA detection, a site-level covariates that scale the sensitivity of eDNA surveys relative to traditional surveys, and gear scaling coefficients for traditional gear types. Models are implemented with a Bayesian framework (Markov chain Monte Carlo) using the Stan probabilistic programming language.

Computes the probability density and cumulative distribution functions of fourteen distributions used for the probabilistic hazard assessment. Estimates the model parameters of the distributions using the maximum likelihood and reports the goodness-of-fit statistics. The recurrence interval estimations of earthquakes are computed for each distribution.

Runs a series of configurable tests against a user's compute environment. This can be used for checking that things like a specific directory or an environment variable is available before you start an analysis. Alternatively, you can use the package's situation report when filing error reports with your compute infrastructure.

This package produces tables for descriptive epidemiological analysis. These tables include attack rates, case fatality ratios, and mortality rates (with appropriate confidence intervals), with additional functionality to calculate Mantel-Haenszel odds, risk, and incidence rate ratios. The methods implemented follow standard epidemiological approaches described in Rothman et al. (2008, ISBN:978-0-19-513554-2). This package is part of the R4EPIs project <https://R4EPI.github.io/sitrep/>.

Can be used to simultaneously estimate networks (Gaussian Graphical Models) in data from different groups or classes via Joint Graphical Lasso. Tuning parameters are selected via information criteria (AIC / BIC / extended BIC) or cross validation.

Density, distribution function, quantile function and random generation for the Kumaraswamy Complementary Weibull Geometric (Kw-CWG) lifetime probability distribution proposed in Afify, A.Z. et al (2017) <doi:10.1214/16-BJPS322>.

Automation of the item selection processes for Rasch scales by means of exhaustive search for suitable Rasch models (dichotomous, partial credit, rating-scale) in a list of item-combinations. The item-combinations to test can be either all possible combinations or item-combinations can be defined by several rules (forced inclusion of specific items, exclusion of combinations, minimum/maximum items of a subset of items). Tests for model fit and item fit include ordering of the thresholds, item fit-indices, likelihood ratio test, Martin-Löf test, Wald-like test, person-item distribution, person separation index, principal components of Rasch residuals, empirical representation of all raw scores or Rasch trees for detecting differential item functioning. The tests, their ordering and their parameters can be defined by the user. For parameter estimation and model tests, functions of the packages eRm', psychotools or pairwise can be used.

This package provides a consistent set of functions for enriching and analyzing sovereign-level economic data. Economists, data scientists, and financial professionals can use the package to add standardized identifiers, demographic and macroeconomic indicators, and derived metrics such as gross domestic product per capita or government expenditure shares.

Simulating multi-arm cluster-randomized, multi-site, and simple randomized trials. Includes functions for conducting multilevel analyses using both Bayesian and Frequentist methods. Supports futility and superiority analyses through Bayesian approaches, along with visualization tools to aid interpretation and presentation of results.

Displays for model fits of multiple models and their ensembles. For classification models, the plots are heatmaps, for regression, scatterplots.

This package provides a predictable and pipeable framework for performing ETL (extract-transform-load) operations on publicly-accessible medium-sized data set. This package sets up the method structure and implements generic functions. Packages that depend on this package download specific data sets from the Internet, clean them up, and import them into a local or remote relational database management system.

Routines for epidemiological contact tracing and visualisation of network of contacts.

This package provides computational methods for detecting adverse high-order drug interactions from individual case safety reports using statistical techniques, allowing the exploration of higher-order interactions among drug cocktails.

This package provides a tidy R client for services implementing the OGC API - Environmental Data Retrieval ('EDR') standard. It is general purpose, but most of its real-world use is against in-situ monitoring networks (stream gauges, weather stations, snow and reservoir telemetry) that expose their stations and time series as EDR collections. Known working endpoints include the USGS waterdata OGC API and the Western Water Datahub'. Provides discovery, query, and parsing helpers for the locations, items, position, area, cube, radius, trajectory, and corridor query types. Returns CoverageJSON as tidy tibble rows and GeoJSON as sf objects.

Offers a set of functions to easily download and clean Brazilian electoral data from the Superior Electoral Court and CepespData websites. Among other features, the package retrieves data on local and federal elections for all positions (city councilor, mayor, state deputy, federal deputy, governor, and president) aggregated by state, city, and electoral zones.

Estimates an ecological niche using occurrence data, covariates, and kernel density-based estimation methods. For a single species with presence and absence data, the envi package uses the spatial relative risk function that is estimated using the sparr package. Details about the sparr package methods can be found in the tutorial: Davies et al. (2018) <doi:10.1002/sim.7577>. Details about kernel density estimation can be found in J. F. Bithell (1990) <doi:10.1002/sim.4780090616>. More information about relative risk functions using kernel density estimation can be found in J. F. Bithell (1991) <doi:10.1002/sim.4780101112>.

This package provides a function to query and extract data from the US Energy Information Administration ('EIA') API V2 <https://www.eia.gov/opendata/>. The EIA API provides a variety of information, in a time series format, about the energy sector in the US. The API is open, free, and requires an access key and registration at <https://www.eia.gov/opendata/>.