It is devoted to Cramer-von Mises goodness-of-fit tests.
    It implements three statistical methods based on Cramer-von Mises statistics to estimate and test a regression model.

Implementation of cross-validation method for testing the forecasting accuracy of several multi-population mortality models. The family of multi-population includes several multi-population mortality models proposed through the actuarial and demography literature. The package includes functions for fitting and forecast the mortality rates of several populations. Additionally, we include functions for testing the forecasting accuracy of different multi-population models.
  References.
  Atance, D., Debon, A., and Navarro, E. (2020) <doi:10.3390/math8091550>.
  Bergmeir, C. & Benitez, J.M. (2012) <doi:10.1016/j.ins.2011.12.028>.
  Debon, A., Montes, F., & Martinez-Ruiz, F. (2011) <doi:10.1007/s13385-011-0043-z>.
  Lee, R.D. & Carter, L.R. (1992) <doi:10.1080/01621459.1992.10475265>.
  Russolillo, M., Giordano, G., & Haberman, S. (2011) <doi:10.1080/03461231003611933>.
  Santolino, M. (2023) <doi:10.3390/risks11100170>.

Cross-validate one or multiple regression and classification models
    and get relevant evaluation metrics in a tidy format. Validate the
    best model on a test set and compare it to a baseline evaluation.
    Alternatively, evaluate predictions from an external model. Currently
    supports regression and classification (binary and multiclass).
    Described in chp. 5 of Jeyaraman, B. P., Olsen, L. R., 
    & Wambugu M. (2019, ISBN: 9781838550134).

Perform canonical variate regression (CVR) for two sets of covariates and a univariate
            response, with regularization and weight parameters tuned by cross validation.

Calculate various cardiovascular disease risk scores from the
    Framingham Heart Study (FHS), the American College of Cardiology (ACC),
    and the American Heart Association (AHA) as described in D’agostino, et al
    (2008) <doi:10.1161/circulationaha.107.699579>, Goff, et al (2013)
    <doi:10.1161/01.cir.0000437741.48606.98>, and Mclelland, et al (2015)
    <doi:10.1016/j.jacc.2015.08.035>.