Calculate the bark beetle phenology based on raster data or
    point-related data. There are multiple models implemented for two bark
    beetle species. The models can be customized and their submodels (onset of
    infestation, beetle development, diapause initiation, mortality) can be
    combined. The following models are available in the package:
    PHENIPS-Clim (first-time release in this package),
    PHENIPS (Baier et al. 2007) <doi:10.1016/j.foreco.2007.05.020>,
    RITY (Ogris et al. 2019) <doi:10.1016/j.ecolmodel.2019.108775>,
    CHAPY (Ogris et al. 2020) <doi:10.1016/j.ecolmodel.2020.109137>,
    BSO (Jakoby et al. 2019) <doi:10.1111/gcb.14766>,
    Lange et al. (2008) <doi:10.1007/978-3-540-85081-6_32>,
    Jönsson et al. (2011) <doi:10.1007/s10584-011-0038-4>.
    The package may be expanded by models for other bark beetle species in the
    future.

Provides the 'C++' header-only library 'barry' for use in R packages. 
 'barry' is a 'C++' template library for counting sufficient statistics on binary 
 arrays and building discrete exponential-family models. It provides tools for 
 sparse arrays, user-defined count statistics, support set constraints, 
 power set generation, and includes modules for Discrete Exponential Family Models 
 (DEFMs) and network statistics. By placing these headers in this package, we 
 offer an efficient distribution system for CRAN as replication of this code in 
 the sources of other packages is avoided. This package follows the same 
 approach as the 'BH' package which provides 'Boost' headers for R packages.

Bayesian Additive Regression Trees (BART) provide flexible nonparametric modeling of covariates for continuous, binary, categorical and time-to-event outcomes.  For more information see Sparapani, Spanbauer and McCulloch <doi:10.18637/jss.v097.i01>.

Contains a variety of methods to generate typical causal inference estimates using Bayesian Additive Regression Trees (BART) as the underlying regression model (Hill (2012) <doi:10.1198/jcgs.2010.08162>).