Automated time series forecasting developed by Microsoft Finance. The Microsoft Finance Time 
    Series Forecasting Framework, aka Finn, can be used to forecast any component of the income 
    statement, balance sheet, or any other area of interest by finance. Any numerical quantity over time, 
    Finn can be used to forecast it. While it can be applied outside of the finance domain, Finn was built 
    to meet the needs of financial analysts to better forecast their businesses within a company, and has 
    a lot of built in features that are specific to the needs of financial forecasters. Happy forecasting!

Access and retrieve vocabulary data 'Finto' API <https://api.finto.fi/>, which is a centralized service for interoperable thesauri, ontology and classification schemes for different subject areas.

R companion to Tsay (2005) Analysis of Financial Time
   Series, second edition (Wiley).  Includes data sets, functions and
   script files required to work some of the examples.  Version 0.3-x
   includes R objects for all data files used in the text and script
   files to recreate most of the analyses in chapters 1-3 and 9 plus
   parts of chapters 4 and 11.

Simplifies the process of importing and managing input-output
  matrices from 'Microsoft Excel' into R, and provides a suite of functions for
  analysis. It leverages the 'R6' class for clean, memory-efficient
  object-oriented programming. Furthermore, all linear algebra computations are
  implemented in 'Rust' to achieve highly optimized performance.

Provides a wrapper for the python module 'FIORA' as well as a 
    'shiny'-App to facilitate data processing and visualization. 'FIORA' allows 
    to predict Mass-Spectra based on the SMILES code of chemical compounds. It 
    is described in the Nature Communications article by Nowatzky (2025) 
    <doi:10.1038/s41467-025-57422-4>.

Provides a lightweight suite
             of functions for retrieving information
             about 5-digit or 2-digit US FIPS codes.