Search and extract data from the Organization for Economic 
    Cooperation and Development (OECD).

Access and Analyze Official Development Assistance (ODA) data using 
    the OECD API <https://gitlab.algobank.oecd.org/public-documentation/dotstat-migration/-/raw/main/OECD_Data_API_documentation.pdf>.
    ODA data includes sovereign-level aid data such as key aggregates (DAC1), geographical
    distributions (DAC2A), project-level data (CRS), and multilateral contributions (Multisystem).

Package for estimating the parameters of a nonlinear function using iterated linearization via Taylor series.  Method is based on  Kubáček (2000) ISBN: 80-244-0093-6. The algorithm is a generalization of the procedure given in Köning, R., Wimmer, G.
             and Witkovský, V. (2014) <doi:10.1088/0957-0233/25/11/115001>.

A collection of general-purpose helper functions that I (and maybe 
    others) find useful when developing data science software. Includes tools 
    for simulation, data transformation, input validation, and more.

Solves penalized least squares problems for big tall data
    using the orthogonalizing EM algorithm of Xiong et al. (2016) 
    <doi:10.1080/00401706.2015.1054436>. The main fitting function is oem() and the
    functions cv.oem() and xval.oem() are for cross validation, the latter being an
    accelerated cross validation function for linear models. The big.oem() function
    allows for out of memory fitting. A description of the underlying methods and 
    code interface is described in Huling and Chien (2022) <doi:10.18637/jss.v104.i06>.

Tools to access data from the data web service of the Oesterreichische Nationalbank (OeNB), <https://www.oenb.at/en/Statistics/User-Defined-Tables/webservice.html>.

Developed to help researchers who need to model the kinetics of carbon dioxide (CO2) production in alcoholic fermentation of wines, beers and other fermented products. The following models are available for modeling the carbon dioxide production curve as a function of time: 5PL, Gompertz and 4PL. This package has different functions, which applied can: perform the modeling of the data obtained in the fermentation and return the coefficients, analyze the model fit and return different statistical metrics, and calculate the kinetic parameters: Maximum production of carbon dioxide; Maximum rate of production of carbon dioxide; Moment in which maximum fermentation rate occurs; Duration of the latency phase for carbon dioxide production; Carbon dioxide produced until maximum fermentation rate occurs. In addition, a function that generates graphs with the observed and predicted data from the models, isolated and combined, is available. Gava, A., Borsato, D., & Ficagna, E. (2020)."Effect of mixture of fining agents on the fermentation kinetics of base wine for sparkling wine production: Use of methodology for modeling". <doi:10.1016/j.lwt.2020.109660>.