Functions to generate and analyze data for psychology experiments based on the General Recognition Theory.

Lightweight way to read 'NumPy' '.npy' and '.npz' files in R. All data types supported
    by 'NumPy', with all sizes (converted internally to R native size), both C and 'Fortran' order,
    and any shape, up to an arbitrary number of dimensions, are supported.

River hydrograph separation and daily runoff time series analysis. Provides
  various filters to separate baseflow and quickflow. Implements advanced separation 
  technique by Rets et al. (2022) <doi:10.1134/S0097807822010146> which involves 
  meteorological data to reveal genetic components of the runoff: ground, rain, thaw 
  and spring (seasonal thaw). High-performance C++17 computation, annually aggregated 
  variables, statistical testing and numerous plotting functions for high-quality 
  visualization.

A tool to sensitivity analysis using SOBOL (Sobol, 1993) and AMA (Dell'Oca et al. 2017 <doi:10.5194/hess-21-6219-2017>) indices.
            It allows to identify the most sensitive parameter or parameters of a model.

Provides utility functions used by the Genome Analysis Toolkit ('GATK') to load tables and plot data. The 'GATK' is a toolkit for variant discovery in high-throughput sequencing data.

Computing Global Sensitivity Indices from given data using Optimal Transport, as defined in Borgonovo et al (2024) <doi:10.1287/mnsc.2023.01796>. You provide an input sample, an output sample, decide the algorithm, and compute the indices.

Write SARIMA models in (finite) AR representation and simulate 
	generalized multiplicative seasonal autoregressive moving average (time) series 
	with Normal / Gaussian, Poisson or negative binomial distribution. 
	The methodology of this method is described in Briet OJT, Amerasinghe PH, and 
	Vounatsou P (2013) <doi:10.1371/journal.pone.0065761>.

Group Sequential Operating Characteristics for Clinical,
        Bayesian two-arm Trials with known Sigma and Normal Endpoints,
	as described in Gerber and Gsponer (2016) <doi: 10.18637/jss.v069.i11>.