Generates bivariate residual plots with simulation polygons for any diagnostics and bivariate model from which functions to extract the desired diagnostics, simulate new data and refit the models are available.

Simulation of bivariate uniform data with a full range of correlations based on 
             two beta densities and computation of the tetrachoric correlation 
             (correlation of bivariate uniform data) from the phi coefficient 
             (correlation of bivariate binary data) and vice versa.

This is a port of the WTC MATLAB package written by Aslak Grinsted
    and the wavelet program written by Christopher Torrence and Gibert P.
    Compo. This package can be used to perform univariate and bivariate
    (cross-wavelet, wavelet coherence, wavelet clustering) analyses.

Compute multivariate location, scale, and correlation
        estimates based on Tukey's biweight M-estimator.

Business days calculations based on a list of holidays and
    nonworking weekdays. Quite useful for fixed income and derivatives pricing.

Maximum likelihood estimation of copula-based zero-inflated 
    (and non-inflated) Poisson and negative binomial count models, based on the 
    article <doi:10.18637/jss.v109.i01>. Supports Frank and Gaussian copulas. 
    Allows for mixed margins (e.g., one margin Poisson, the other zero-inflated 
    negative binomial), and several marginal link functions. Built-in methods for 
    publication-quality tables using 'texreg', post-estimation diagnostics using 
    'DHARMa', and testing for marginal zero-modification via <doi:10.1177/0962280217749991>. 
    For information on copula regression for count data, see Genest and Nešlehová (2007) 
    <doi:10.1017/S0515036100014963> as well as Nikoloulopoulos (2013) <doi:10.1007/978-3-642-35407-6_11>. 
    For information on zero-inflated count regression generally, see Lambert (1992) 
    <https://www.jstor.org/stable/1269547>. The author acknowledges 
    support by NSF DMS-1925119 and DMS-212324.