A toolkit for Commodities 'analytics', risk management and
    trading professionals. Includes functions for API calls to
    <https://commodities.morningstar.com/#/>, <https://developer.genscape.com/>,
    and <https://www.bankofcanada.ca/valet/docs>.

Provide seamless support for right-to-left (RTL) languages, such as Persian and Arabic,
  in R Markdown documents and 'LaTeX' output. It includes functions and hooks that enable easy
  integration of RTL language content, allowing users to create documents that adhere to RTL writing
  conventions. For in-depth insights into dynamic documents and the 'knitr' package, consider referring
  to Xie, Y (2014) <ISBN: 978-1-482-20353-0>.

Convenience functions to make some common tasks with right-to-left string
    printing easier, more convenient and with no need to remember long Unicode
    characters. Specifically helpful for right-to-left languages such as Arabic,
    Persian and Hebrew.

Terrestrial laser scanning (TLS) data processing and post-hurricane damage severity classification at the individual tree level using deep Learning. Further details were published in Klauberg et al. (2023) <doi:10.3390/rs15041165>.

Native 'R' interface to 'TMB' (Template Model Builder) so models can be written entirely in 'R' rather than 'C++'. Automatic differentiation, to any order, is available for a rich subset of 'R' features, including linear algebra for dense and sparse matrices, complex arithmetic, Fast Fourier Transform, probability distributions and special functions. 'RTMB' provides easy access to model fitting and validation following the principles of Kristensen, K., Nielsen, A., Berg, C. W., Skaug, H., & Bell, B. M. (2016) <DOI:10.18637/jss.v070.i05> and Thygesen, U.H., Albertsen, C.M., Berg, C.W. et al. (2017) <DOI:10.1007/s10651-017-0372-4>.

Extends the functionality of the 'RTMB' <https://kaskr.r-universe.dev/RTMB> package by providing a collection of non-standard probability distributions compatible with automatic differentiation (AD). While 'RTMB' enables flexible and efficient modelling, including random effects, its built-in support is limited to standard distributions. The package adds additional AD-compatible distributions, broadening the range of models that can be implemented and estimated using 'RTMB'. Automatic differentiation and Laplace approximation are described in Kristensen et al. (2016) <doi:10.18637/jss.v070.i05>.