Implements wild bootstrap tests for autocorrelation in Vector
    Autoregressive (VAR) models based on Ahlgren and Catani (2016)
    <doi:10.1007/s00362-016-0744-0>, a combined Lagrange Multiplier (LM)
    test for Autoregressive Conditional Heteroskedasticity (ARCH) in VAR
    models from Catani and Ahlgren (2016) <doi:10.1016/j.ecosta.2016.10.006>,
    and bootstrap-based methods for determining the cointegration rank from
    Cavaliere, Rahbek, and Taylor (2012) <doi:10.3982/ECTA9099> and
    Cavaliere, Rahbek, and Taylor (2014) <doi:10.1080/07474938.2013.825175>.

Implements a maximum likelihood estimation (MLE) method for
    estimation and prediction of Gaussian process-based spatially varying
    coefficient (SVC) models (Dambon et al. (2021a)
    <doi:10.1016/j.spasta.2020.100470>).  Covariance tapering (Furrer et
    al. (2006) <doi:10.1198/106186006X132178>) can be applied such that
    the method scales to large data. Further, it implements a joint
    variable selection of the fixed and random effects (Dambon et al.
    (2021b) <doi:10.1080/13658816.2022.2097684>). The package and its 
    capabilities are described in (Dambon et al. (2021c)
    <doi:10.48550/arXiv.2106.02364>).

Provide a collection of miscellaneous R functions
    related to the Vasicek distribution with the intent to make
    the lives of risk modelers easier.

Provides probability density, cumulative distribution,
    quantile, and random number generation functions for the Vasicek
    distribution. In addition, two functions are available for fitting
    Generalized Additive Models for Location, Scale and Shape introduced
    by Rigby and Stasinopoulos (2005,
    <doi:10.1111/j.1467-9876.2005.00510.x>). Some functions are written in
    'C++' using 'Rcpp', developed by Eddelbuettel and Francois (2011,
    <doi:10.18637/jss.v040.i08>).

An R client for the 'vatcheckapi.com' VAT number validation API. The API requires registration of an API key. Basic features are free, some require a paid subscription. You can find the full API documentation at <https://vatcheckapi.com/docs> .