An overall test for seasonality of a given time
    series in addition to a set of individual seasonality tests as
    described by Ollech and Webel (forthcoming): An overall seasonality
    test. Bundesbank Discussion Paper.

Provides tools for processing and evaluating seasonal weather forecasts, 
    with an emphasis on tercile forecasts. We follow the World Meteorological Organization's 
    "Guidance on Verification of Operational Seasonal Climate Forecasts", 
    S.J.Mason (2018, ISBN: 978-92-63-11220-0, URL: <https://library.wmo.int/idurl/4/56227>). 
    The development was supported by the European Union’s Horizon 2020 research and innovation 
    programme under grant agreement no. 869730 (CONFER).
    A comprehensive online tutorial is available at <https://seasonalforecastingengine.github.io/SeaValDoc/>.

Monte Carlo sampling algorithms for semiparametric
    Bayesian regression analysis. These models feature a nonparametric
    (unknown) transformation of the data paired with widely-used
    regression models including linear regression, spline regression,
    quantile regression, and Gaussian processes. The transformation
    enables broader applicability of these key models, including for
    real-valued, positive, and compactly-supported data with challenging
    distributional features. The samplers prioritize computational
    scalability and, for most cases, Monte Carlo (not MCMC) sampling for
    greater efficiency. Details of the methods and algorithms are provided
    in Kowal and Wu (2024) <doi:10.1080/01621459.2024.2395586>.

These functions were developed within SECFISH project (Strengthening regional cooperation in the area of fisheries  data collection-Socio-economic data collection for fisheries, aquaculture and the processing industry at EU level). They are aimed at identifying  correlations between costs and transversal variables by metier using individual vessel data and for disaggregating variable costs from  fleet segment to metier  level.

Estimating parameters of site clusters on 2D & 3D square lattice with various lattice sizes, relative fractions of open sites (occupation probability), iso- & anisotropy, von Neumann & Moore (1,d)-neighborhoods, described by Moskalev P.V. et al. (2011) <arXiv:1105.2334v1>.