Inflation Decomposition, Core Measures, and Trend Estimation

Tools for analysing inflation dynamics. Computes weighted contributions of price index components, core inflation measures (trimmed mean, weighted median, exclusion-based) following Bryan and Cecchetti (1994) , inflation persistence via sum-of-AR-coefficients, diffusion indices, Phillips curve estimation, breakeven inflation, and trend inflation using the Beveridge-Nelson decomposition and Hodrick-Prescott filter. All functions are pure computation and work with price data from any source.

Yield Curve Fitting, Analysis, and Decomposition

Fits yield curves using Nelson-Siegel (1987) , Svensson (1994) , and cubic spline methods. Extracts forward rates, discount factors, and par rates from fitted curves. Computes duration and convexity risk measures. Computes Z-spread and key rate durations. Provides principal component decomposition following Litterman and Scheinkman (1991) , carry and roll-down analysis, and slope measures. All methods are pure computation with no external dependencies beyond base R; works with yield data from any source.

Inflation Adjustment for Historical Currency Values

Convert historical monetary values into their present-day equivalents using bundled CPI (Consumer Price Index) and GDP deflator data sourced from the World Bank Development Indicators. Supports British pounds (GBP), Australian dollars (AUD), US dollars (USD), Euro (EUR), Canadian dollars (CAD), Japanese yen (JPY), Chinese yuan (CNY), Swiss francs (CHF), New Zealand dollars (NZD), Indian rupees (INR), South Korean won (KRW), Brazilian reais (BRL), and Norwegian krone (NOK). Currency codes and country names are both accepted as input.

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. Data is downloaded directly from the AEC < https://results.aec.gov.au> on first use and cached locally for subsequent calls.

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.

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 Welfare Trends Report (incapacity benefit spending and caseloads), and the Fiscal Risks and Sustainability Report (50-year state pension projections). 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 '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'.

Discriminative Random Walk with Restart

We present DRaWR, a network-based method for ranking genes or properties related to a given gene set. Such related genes or properties are identified from among the nodes of a large, heterogeneous network of biological information. Our method involves a random walk with restarts, performed on an initial network with multiple node and edge types, preserving more of the original, specific property information than current methods that operate on homogeneous networks. In this first stage of our algorithm, we find the properties that are the most relevant to the given gene set and extract a subnetwork of the original network, comprising only the relevant properties. We then rerank genes by their similarity to the given gene set, based on a second random walk with restarts, performed on the above subnetwork.

Access 'European Central Bank' Data

Provides clean, tidy access to statistical data published by the 'European Central Bank' ('ECB') via the 'ECB Data Portal' API < https://data.ecb.europa.eu>. Covers policy interest rates, 'EURIBOR', euro exchange rates, harmonised consumer price inflation ('HICP'), euro area yield curves, the euro short-term rate ('ESTR'), monetary aggregates (M1, M2, M3), mortgage and lending rates, GDP, unemployment, and government debt-to-GDP. Each dataset has a dedicated function that abstracts away the underlying 'SDMX' key structure, so users do not need to know series codes. A generic fetcher is also provided for direct access to any of the 'ECB' 100-plus dataflows. Data is downloaded 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.