simulations, forecasting, and estimation of generalized impulse response function and generalized

Title: Estimate Gaussian or Student's t Mixture Vector Autoregressive
Gaussian mixture vector autoregressive, Student's t mixture vector autoregressive, and Gaussian and Student's t
mixture vector autoregressive models, quantile residual tests, graphical diagnostics,

Title: Estimate Gaussian and Student's t Mixture Vector Autoregressive

Title: Generalized Method of Wavelet Moments
person("James", "Balamuta", , "james.balamuta@gmail.com", c("aut", "cph")),
person("Stephane", "Guerrier", , "stephane@illinois.edu", c("ctb","cre","cph")),
person("Roberto", "Molinari", , "roberto.molinari@unige.ch", c("ctb", "cph")),
person("Wenchao", "Yang", , "wyang40@illinois.edu", c("ctb"))
Description: Generalized Method of Wavelet Moments (GMWM) is an estimation technique for the parameters of time series models. It uses the wavelet variance in a moment matching approach that makes it particularly suitable for the estimation of certain state-space models. Furthermore, there exists a robust implementation of GMWM, which allows the robust estimation of some state-space models and ARIMA models. Lastly, the package provides the ability to quickly generate time series data, perform different wavelet decompositions, and visualizations.
Imports: Rcpp (>= 0.11.3), scales, grid, reshape2, gridExtra, devtools,
utils, stats, methods, graphics, grDevices

Description: Generalized Method of Wavelet Moments (GMWM) is an estimation
technique for the parameters of time series models. It uses the wavelet variance
in a moment matching approach that makes it particularly suitable for the
estimation of certain state-space models. Furthermore, there exists a robust
implementation of GMWM, which allows the robust estimation of some state-space
models and ARIMA models. Lastly, the package provides the ability to quickly
generate time series data, perform different wavelet decompositions, and
Imports: Rcpp (>= 0.12.2), scales, grid, reshape2, utils, stats,
Suggests: testthat, knitr, rmarkdown, imudata