Access 'Office for Budget Responsibility' Data

Provides clean, tidy access to data published by the 'Office for Budget Responsibility' ('OBR'), the UK's independent fiscal watchdog. Covers the Public Finances Databank (outturn for PSNB, PSND, receipts, and expenditure since 1946), the Historical Official Forecasts Database (every 'OBR' forecast since 2010), the Economic and Fiscal Outlook detailed forecast tables (five-year projections from the latest Budget), the monthly profiles for the public finances (the 'OBR' forecast apportioned across the months of the fiscal year), and the Welfare Trends Report (incapacity benefit spending and caseloads). All returned objects carry provenance metadata recording the source URL, publication vintage, retrieval time, and file fingerprint, so analyses can be audited and reproduced. Data is downloaded from the 'OBR' on first use and cached locally for subsequent calls. Data is sourced from the 'OBR' website < https://obr.uk>.

Access Australian Electoral Commission Data

Provides clean, tidy access to Australian Electoral Commission (AEC) federal election data. Includes results for the House of Representatives and Senate from 2007 onwards, at both division and polling place level, plus by-elections from 2008 onwards, the 2023 referendum, and the full distribution of preferences. Data is downloaded directly from the AEC < https://results.aec.gov.au> on first use and cached locally for subsequent calls.

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.

Download and Tidy Data from the 'OECD'

Provides clean, tidy access to key economic indicators published by the 'Organisation for Economic Co-operation and Development' ('OECD'), covering GDP, CPI inflation, unemployment, tax revenue, government deficit, health expenditure, education expenditure, income inequality, labour productivity, and current account balance across all 38 'OECD' member countries. Data is downloaded from the 'OECD Data Explorer' API < https://data-explorer.oecd.org> on first use and cached locally for subsequent calls. Returns tidy long-format data frames ready for analysis and visualisation.

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.

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) .

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/support/access-data-service-api-user-documentation>. 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'.

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, Gammerman, and Shafer 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.

Monetary Policy Shock Series for Empirical Macroeconomics

Provides a curated multi-country collection of monetary policy shock and stance series from the empirical macroeconomics literature, bundled as tidy data frames with provenance metadata. Version 0.1.0 includes thirteen series covering the United States, United Kingdom, and Australia: for the US, the policy news shock of Nakamura and Steinsson (2018) , the orthogonalised surprise of Bauer and Swanson (2023) , the target and path factors of the Swanson (2021) extension of Gurkaynak, Sack, and Swanson (2005), the pure monetary policy and central bank information shocks of Jarocinski and Karadi (2020) , the informationally-robust shock of Miranda-Agrippino and Ricco (2021) , and the shadow federal funds rate of Wu and Xia (2016) ; for the UK, the UK Monetary Policy Event-Study Database of Braun, Miranda-Agrippino, and Saha (2025) , the high-frequency surprise of Cesa-Bianchi, Thwaites, and Vicondoa (2020) , and the narrative shock of Cloyne and Hurtgen (2016) ; for Australia, the three-component RBA surprise of Hambur and Haque (2023) and the credit-spread-augmented RBA narrative shock of Beckers (2020). Helpers support date alignment, frequency conversion, and shock cumulation. All data is bundled; no runtime network access is required.

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.