Description: 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.

Title: Conduct Univariate and Bivariate Wavelet Analyses
Description: 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.

Author: Tarik C. Gouhier, Aslak Grinsted, Viliam Simko
Imports: fields, foreach, Rcpp (>= 0.12.2)

Suggests: testthat, knitr, rmarkdown, devtools, profvis, microbenchmark

Title: Compute the Biweight Mean Vector and Covariance & Correlation
Description: Compute multivariate location, scale, and correlation
estimates based on Tukey's biweight M-estimator.

Title: Functions to compute the biweight mean vector and covariance &

Title: Functions to handle business days calculations
Description: bizdays is a small set of functions to help with calculations
which make use of business days. It works based on a list of holidays
which is passed as an argument. Its interface is simple and flexible
bizdays can be fairly used for fixed income calculations.
Many countries make intense use of business days to price
financial instruments, like bonds and derivatives.

Title: Business Days Calculations and Utilities
Description: Business days calculations based on a list of holidays and
nonworking weekdays. Quite useful for fixed income and derivatives pricing.

Suggests: RQuantLib, timeDate, knitr, testthat, covr, rmarkdown

Suggests: RQuantLib, timeDate, knitr, testthat

Suggests: RQuantLib, timeDate, knitr, testthat, covr

Title: Bivariate Zero-Inflated Count Models Using Copulas
person("John", "Niehaus", , "jniehaus2257@gmail.com", role = c("aut", "cre"))
Description: Maximum likelihood estimation of copula-based zero-inflated
(and non-inflated) Poisson and negative binomial count models. 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', and post-estimation
diagnostics using 'DHARMa'. 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?origin=crossref>. The author
acknowledges support by NSF DMS-1925119 and DMS-212324.