Collect  your data on digital marketing campaigns from 'Facebook Organic' using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.

Provides an interface to the 'Kairos' Face Recognition API <https://kairos.com/face-recognition-api>. The API detects faces in images and returns estimates for demographics like gender, ethnicity and age.

Calculate useful quantities for a user-defined differential equation
    model of infectious disease transmission among individuals in a healthcare
    facility. Input rates of transition between states of individuals with and
    without the disease-causing organism, distributions of states at facility
    admission, relative infectivity of transmissible states, and the facility length
    of stay distribution. Calculate the model equilibrium and the basic facility
    reproduction number, as described in Toth et al. (2025) 
    <doi:10.1371/journal.pcbi.1013577>.

Linear cross-section factor model fitting with least-squares 
    and robust fitting the 'lmrobdetMM()' function from 'RobStatTM'; related
    volatility, Value at Risk and Expected Shortfall risk and performance 
    attribution (factor-contributed vs idiosyncratic returns);
    tabular displays of risk and performance reports;
    factor model Monte Carlo. The package authors would like to thank Chicago
    Research on Security Prices,LLC for the cross-section of about 300
    CRSP stocks data (in the data.table object 'stocksCRSP', and S&P GLOBAL MARKET
    INTELLIGENCE for contributing 14 factor scores (a.k.a "alpha factors".and
    "factor exposures") fundamental data on the 300 companies in the data.table
    object 'factorSPGMI'.  The 'stocksCRSP' and 'factorsSPGMI' data are not covered by
    the GPL-2 license, are not provided as open source of any kind, and they are
    not to be redistributed in any form.

Supports teaching methods of estimating and testing time series
    factor models for use in robust portfolio construction and analysis. Unique
    in providing not only classical least squares, but also modern robust model
    fitting methods which are not much influenced by outliers. Includes
    returns and risk decompositions, with user choice of  standard deviation,
    value-at-risk, and expected shortfall risk measures. "Robust Statistics
    Theory and Methods (with R)", R. A. Maronna, R. D. Martin, V. J. Yohai, 
    M. Salibian-Barrera (2019) <doi:10.1002/9781119214656>.