Estimates optimal classification (Poole 2000) <doi:10.1093/oxfordjournals.pan.a029814>
		scores from roll call votes supplied though a 'rollcall'
		object from package 'pscl'.

Computes optimal capital allocations based on some standard principles such as Haircut, Overbeck type II and the Covariance Allocation Principle. It also provides some shortcuts for obtaining the Value at Risk and the Expectation Shortfall, using both the normal and the t-student distribution, see Urbina and Guillén (2014)<doi:10.1016/j.eswa.2014.05.017> and Urbina (2013)<http://hdl.handle.net/2099.1/19443>.

Generic function for estimating positron emission tomography (PET) neuroreceptor occupancies from the total volumes of distribution of a set of regions of interest. Fittings methods include the simple 'reference region' and 'ordinary least squares' (sometimes known as occupancy plot) methods, as well as the more efficient 'restricted maximum likelihood estimation'.

Facilitates the gathering of biodiversity occurrence data 
  from disparate sources. Metadata is managed throughout the process to facilitate 
  reporting and enhanced ability to repeat analyses.

Fits multispecies site occupancy models to environmental DNA
    metabarcoding data collected using spatially-replicated survey design.
    Model fitting results can be used to evaluate and compare the effectiveness
    of species detection to find an efficient survey design.
    Reference: Fukaya et al. (2022) <doi:10.1111/2041-210X.13732>.

The classical and extended occupancy distributions occur in cases where balls are randomly allocated 
    to bins. The PDF, CDF, quantile functions, generation of random variates, and calculating 
    the first four central moments of the distributions are implemented as described in 
    O’Neill (2019) <doi:10.1080/00031305.2019.1699445>.

Perform interactive occupation coding during interviews as
    described in Peycheva, D., Sakshaug, J., Calderwood, L. (2021) <doi:10.2478/jos-2021-0042>
    and Schierholz, M., Gensicke, M., Tschersich, N., Kreuter, F. (2018) <doi:10.1111/rssa.12297>.
    Generate suggestions for occupational categories based on free text
    input, with pre-trained machine learning models in German and a ready-to-use
    shiny application provided for quick and easy data collection.