The main objective of cooperative games is to allocate a good among
  the agents involved. This package includes the most well-known   allocation 
  rules, i.e., the Shapley value, the Banzhaf value, the egalitarian rule, and 
  the equal surplus division value. In addition, it considers the point of view 
  of a priori unions (situations in which agents can form coalitions). For this
  purpose, the package includes the Owen value, the Banzhaf-Owen value, and the
  corresponding extensions of the egalitarian rules. All these values can be 
  calculated exactly or estimated by sampling.

The model, developed at the Vienna University of Technology, is a lumped conceptual rainfall-runoff model, following the structure of the HBV model. 
             The model can also be run in a semi-distributed fashion and with dual representation of soil layer.
             The model runs on a daily or shorter time step and consists of a snow routine, a soil moisture routine and a flow routing routine. 
             See Parajka, J., R. Merz, G. Bloeschl (2007) <DOI:10.1002/hyp.6253> Uncertainty and multiple objective calibration in regional water balance modelling: case study in 320 Austrian catchments, Hydrological Processes, 21, 435-446.

Create a time-varying dataset using features, exposure, and
    look back specifications.

Fit of a double additive cure survival model with time-varying covariates. The additive terms in the long- and short-term survival submodels, modelling the cure probability and the event timing for susceptible units, are estimated using Laplace P-splines. For more details, see Lambert and Kreyenfeld (2025) <doi:10.1093/jrsssa/qnaf035>.

Total variation denoising can be used to approximate a given
    sequence of noisy observations by a piecewise constant sequence, with 
    adaptively-chosen break points. An efficient linear-time algorithm for 
    total variation denoising is provided here, based on Johnson (2013)
    <doi:10.1080/10618600.2012.681238>.

Fits time-varying effect models (TVEM). These are a kind of application of varying-coefficient models in the context of longitudinal data, allowing the strength of linear, logistic, or Poisson regression relationships to change over time.  These models are described further in Tan, Shiyko, Li, Li & Dierker (2012) <doi:10.1037/a0025814>.  We thank Kaylee Litson, Patricia Berglund, Yajnaseni Chakraborti, and Hanjoo Kim for their valuable help with testing the package and the documentation. The development of this package was part of a research project supported by National Institutes of Health grants P50 DA039838 from the National Institute of Drug Abuse and 1R01 CA229542-01 from the National Cancer Institute and the NIH Office of Behavioral and Social Science Research. Content is solely the responsibility of the authors and does not necessarily represent the official views of the funding institutions mentioned above. This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.