Implements the multivariate adaptive shrinkage (mash)
    method of Urbut et al (2019) <DOI:10.1038/s41588-018-0268-8> for
    estimating and testing large numbers of effects in many conditions
    (or many outcomes). Mash takes an empirical Bayes approach to
    testing and effect estimation; it estimates patterns of similarity
    among conditions, then exploits these patterns to improve accuracy
    of the effect estimates. The core linear algebra is implemented in
    C++ for fast model fitting and posterior computation.

Maximum likelihood estimation for series systems where the
    component cause of failure is masked. Implements analytical log-likelihood,
    score, and Hessian functions for exponential, homogeneous Weibull, and
    heterogeneous Weibull component lifetimes under masked cause conditions
    (C1, C2, C3). Supports exact, right-censored, left-censored, and
    interval-censored observations via composable observation functors.
    Provides random data generation, model fitting, and Fisher information
    for asymptotic inference. See Lin, Loh, and Bai (1993)
    <doi:10.1109/24.257799> and Craiu and Reiser (2006)
    <doi:10.1111/j.1541-0420.2005.00498.x>.

Likelihood-based inference for series systems with masked
    component cause of failure, using arbitrary dynamic failure rate
    component distributions. Computes log-likelihood, score, Hessian, and
    maximum likelihood estimates for masked data satisfying conditions
    C1, C2, C3 under general component hazard functions. Implements the
    'series_md' protocol defined in the 'maskedcauses' package.

Create vectors with sticky flags for elements that should not be
    displayed. Numeric vectors have basic subset and arithmetic methods
    implemented.

Mask ranges based on expert 
    knowledge or remote sensing layers. These tools can 
    be combined to quantitatively and reproducibly 
    generate a new map or to update an existing map.
    Methods include expert opinion and data-driven 
    tools to generate thresholds for binary masks.