A 'RESTful' API wrapper for accessing the 'GENESIS' database
    of the German Federal Statistical Office (Destatis)
    <https://www-genesis.destatis.de/>. Also supports data search
    functions, credential management, result caching, and handling remote
    background jobs for large datasets.

Duplicated restaurant data (pre-processed and formatted) for entity resolution. This package contains formatted data from a data set that contains information about different restaurants, with the Zagats portion containing 331 records and the Fodors portion containing 533 records. The following variables are included in the data set: id, name, address, city, phone, type. The data set has a respective gold data set that provides information on which records match based on id.

Download large sections of
    'GenBank' <https://www.ncbi.nlm.nih.gov/genbank/> and generate a local
    SQL-based database. A user can then query this database using 'restez'
    functions or through 'rentrez' <https://CRAN.R-project.org/package=rentrez>
    wrappers.

Models a RESTful service as if it were a nested R list.

Provides the user with functions to develop their trading strategy,
    uncover actionable trading ideas, and monitor consensus shifts with
    crowdsourced earnings and economic estimate data directly from
    <www.estimize.com>. Further information regarding the web services this
    package invokes can be found at <www.estimize.com/api>.

Implementation of the RESTK algorithm based on Markov's Inequality from  Vilardell, Sergi, Serra, Isabel, Mezzetti, Enrico, Abella, Jaume, Cazorla, Francisco  J. and Del Castillo, J. (2022). "Using Markov's Inequality with Power-Of-k Function for Probabilistic WCET Estimation". In 34th Euromicro Conference on Real-Time Systems (ECRTS 2022). Leibniz International Proceedings in Informatics (LIPIcs) 231 20:1-20:24. <doi:10.4230/LIPIcs.ECRTS.2022.20>. This work has been supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 772773).