Generates region-specific Suess and Laws corrections for 
    stable carbon isotope data from marine organisms collected between 1850 and 2023. Version
    0.1.6 of 'SuessR' contains four built-in regions: the Bering Sea ('Bering Sea'), the
    Aleutian archipelago ('Aleutian Islands'), the Gulf of Alaska ('Gulf of Alaska'), and the 
    subpolar North Atlantic ('Subpolar North Atlantic'). Users can supply their own environmental 
    data for regions currently not built into the package to generate corrections for those regions.

The sufficient forecasting (SF) method is implemented by this package for a single time series forecasting using many predictors and a possibly nonlinear forecasting function. Assuming that the predictors are driven by some latent factors, the SF first conducts factor analysis and then performs sufficient dimension reduction on the estimated factors to derive predictive indices for forecasting. The package implements several dimension reduction approaches, including principal components (PC), sliced inverse regression (SIR), and directional regression (DR). Methods for dimension reduction are as described in: Fan, J., Xue, L. and Yao, J. (2017) <doi:10.1016/j.jeconom.2017.08.009>, Luo, W., Xue, L., Yao, J. and Yu, X. (2022) <doi:10.1093/biomet/asab037> and Yu, X., Yao, J. and Xue, L. (2022) <doi:10.1080/07350015.2020.1813589>.

Create a hexagon tile map display from spatial polygons. Each 
    polygon is represented by a hexagon tile, placed as close to it's original
    centroid as possible, with a focus on maintaining spatial relationship to
    a focal point. Developed to aid visualisation and analysis of spatial 
    distributions across Australia, which can be challenging due to the 
    concentration of the population on the coast and wide open interior.

Provides 'ggplot2' extensions to construct glyph-maps for visualizing seasonality in spatiotemporal data. See the Journal of Statistical Software reference: Zhang, H. S., Cook, D., Laa, U., Langrené, N., & Menéndez, P. (2024) <doi:10.18637/jss.v110.i07>. The manuscript for this package is currently under preparation and can be found on GitHub at <https://github.com/maliny12/paper-sugarglider>.