Access 'Federal Reserve Economic Data'

Provides clean, tidy access to economic data from the 'Federal Reserve Economic Data' ('FRED') API < https://fred.stlouisfed.org/docs/api/fred/>. 'FRED' is maintained by the 'Federal Reserve Bank of St. Louis' and contains over 800,000 time series from 118 sources covering GDP, employment, inflation, interest rates, trade, and more. Dedicated functions fetch series observations, search for series, browse categories, releases, and tags, and retrieve series metadata. Multiple series can be fetched in a single call. Server-side unit transformations (percent change, log, etc.) and frequency aggregation are supported. Data is cached locally for subsequent calls. This product uses the 'FRED' API but is not endorsed or certified by the 'Federal Reserve Bank of St. Louis'.

Wrangling Longitudinal Survival Data

Streamlines the process of transitioning between data formats commonly used in survival analysis. Functions convert longitudinal data between formats used as input for survival models as well as support overall preparation. Users are able to focus on model building rather than data wrangling.

Clustering Communication Networks Using the Stochastic Topic Block Model Through Linkage.fr

It allows to cluster communication networks using the Stochastic Topic Block Model by posting jobs through the API of the linkage.fr server, which implements the clustering method. The package also allows to visualize the clustering results returned by the server.

Process and Visualize Evolve & Resequence Experiments

Handle data from evolve and resequence experiments. Measured allele frequencies (e.g., from variants called from high-throughput sequencing data) are compared using an update of the PsiSeq algorithm (Earley, Eric and Corbin Jones (2011) ). Functions for saving and loading important files are also included, as well as functions for basic data visualization.

Conformal Prediction and Uncertainty Quantification

Implements conformal prediction methods for constructing prediction intervals (regression) and prediction sets (classification) with finite-sample coverage guarantees. Methods include split conformal, 'CV+' and 'Jackknife+' (Barber et al. 2021) , 'Conformalized Quantile Regression' (Romano et al. 2019) , 'Adaptive Prediction Sets' (Romano, Sesia, Candes 2020) , 'Regularized Adaptive Prediction Sets' (Angelopoulos et al. 2021) , Mondrian conformal prediction for group-conditional coverage (Vovk et al. 2005), weighted conformal prediction for covariate shift (Tibshirani et al. 2019), and adaptive conformal inference for sequential prediction (Gibbs and Candes 2021). All methods are distribution-free and provide calibrated uncertainty quantification without parametric assumptions. Works with any model that can produce predictions from new data, including 'lm', 'glm', 'ranger', 'xgboost', and custom user-defined models.

Access 'NOAA' Climate and Weather Data

Provides clean, tidy access to climate and weather data from the 'National Oceanic and Atmospheric Administration' ('NOAA') via the 'National Centers for Environmental Information' ('NCEI') Data Service API < https://www.ncei.noaa.gov/access/services/data/v1>. Covers daily weather observations, monthly and annual summaries, and 30-year climate normals from over 100,000 stations across 180 countries. No API key is required. Dedicated functions handle the most common datasets, while a generic fetcher provides access to all 'NCEI' datasets. Station discovery functions help users find stations by location or name. Data is downloaded on first use and cached locally for subsequent calls. This package is not endorsed or certified by 'NOAA'.

Economic Nowcasting with Bridge Equations and Real-Time Evaluation

Provides bridge equations with optional autoregressive terms for nowcasting low-frequency macroeconomic variables (e.g. quarterly GDP) from higher-frequency indicators (e.g. monthly retail sales). Handles the ragged-edge problem where different indicators have different publication lags via mixed-frequency alignment. Includes pseudo-real-time evaluation with expanding or rolling windows, and the Diebold-Mariano test for comparing forecast accuracy following Harvey, Leybourne, and Newbold (1997) . No API calls; designed to work with data from any source.

Nonparametric Rotations for Sphere-Sphere Regression

Fits sphere-sphere regression models by estimating locally weighted rotations. Simulation of sphere-sphere data according to non-rigid rotation models. Provides methods for bias reduction applying iterative procedures within a Newton-Raphson learning scheme. Cross-validation is exploited to select smoothing parameters. See Marco Di Marzio, Agnese Panzera & Charles C. Taylor (2018) .

Tools for Trade Practitioners

A collection of tools for trade practitioners, including the ability to calibrate different consumer demand systems and simulate the effects of tariffs and quotas under different competitive regimes. These tools are derived from Anderson et al. (2001) and Froeb et al. (2003) .

Provides a Link Between the 'LSEG Datastream' System and R

Provides a set of functions and a class to connect, extract and upload information from the 'LSEG Datastream' database. This package uses the 'DSWS' API and server used by the 'Datastream DFO addin'. Details of this API are available at < https://www.lseg.com/en/data-analytics>. Please report issues at < https://github.com/CharlesCara/DatastreamDSWS2R/issues>.