Provides methods for reading, displaying,
    processing and writing files originally arranged for
    the 'DSSAT-CSM' fixed width format. The 'DSSAT-CSM' 
    cropping system model is described at J.W. Jones,
    G. Hoogenboomb, C.H. Porter, K.J. Boote, W.D. Batchelor,
    L.A. Hunt, P.W. Wilkens, U. Singh, A.J. Gijsman, 
    J.T. Ritchie (2003) <doi:10.1016/S1161-0301(02)00107-7>.

Tools for spatio-temporal disaggregation of areal data across multiple 
    time points, including support for changing polygon boundaries. Implements 
    methods for spatially aggregated log-Gaussian Cox process models with 
    changing areal boundaries as described in Ripstein, Brown and Stafford 
    (2026) "Spatio-Temporal Disaggregation with Changing Areal Boundaries" 
    <doi:10.48550/arXiv.2606.25074>. Combines polygon-level 
    observations, population rasters and optional covariate rasters to infer fine-scale 
    spatial fields over time. Models can be efficiently fit using 'TMB' (Template Model 
    Builder) and adaptive Gauss-Hermite quadrature for fast approximate inference
    or via 'tmbstan' for MCMC.

An implementation of common higher order functions with syntactic
    sugar for anonymous function. Provides also a link to 'dplyr' and
    'data.table' for common transformations on data frames to work around non
    standard evaluation by default.

Validates data frames against a defined schema. Produces a report of the checks performed and any issues found, with index and entry value where appropriate. Backend checks are performed using pointblank Richard Iannone et al (2025) <doi:10.32614/CRAN.package.pointblank>.

Provides an interface to the 'Apache DataSketches'
    (<https://datasketches.apache.org/>) library of streaming algorithms for
    approximate analytics on data too large to hold or process exactly.
    Sketches are compact, mergeable summaries built in a single pass over a
    stream that answer queries such as approximate distinct counts, quantiles
    and ranks, frequent items and point-frequency estimates, weighted sampling,
    and set membership with mathematically proven error bounds. Implements
    Karnin-Lang-Liberty (KLL), Relative Error
    Quantiles (REQ), t-Digest, HyperLogLog (HLL), Compressed Probabilistic
    Counting (CPC), Theta, Frequent Items, Count-Min, Array of Doubles,
    Variance Optimal (VarOpt), Exact and Bounded Probabilistic
    Proportional-to-Size (EBPPS), and Bloom filter sketches, with native
    serialization for interoperability with other 'Apache DataSketches'
    implementations.