Description: Simulate data sets given a dependence model, validate
graphical models using the bootstrap, find the best prediction
Depends: grid, epitools, mimR, CoCo, CoCoObjects, CoCoRaw, CoCoCore,
Packaged: Thu Nov 8 10:01:54 2007; sobotka

Depends: R (>= 2.7.0), grid, epitools, CoCo, CoCoObjects, CoCoRaw,
Packaged: Mon Jul 28 10:57:07 2008; hornik

Description: Simulate data sets given a dependence model,
validate graphical models using the bootstrap,
find the best prediction model using cross validation.
Depends: R (>= 2.7.0), grid, epitools, CoCo, CoCoObjects, CoCoRaw, CoCoCore, gtools
Packaged: Fri Dec 19 14:19:02 2008; sobotka

Depends: R (>= 2.10.0), grid, epitools, gtools
Packaged: 2012-10-18 14:02:55 UTC; fabiansobotka

Title: Estimate Gaussian Mixture Vector Autoregressive Model
Authors@R: person("Savi", "Virolainen", email = "savi.virolainen@helsinki.fi", role = c("aut", "cre"))
Description: Maximum likelihood estimation of Gaussian Mixture Vector Autoregressive (GMVAR)
model, quantile residual tests, graphical diagnostics, forecasting and simulations. Applying
general linear constraints to the autoregressive parameters is supported.
Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2016) <doi:10.1016/j.jeconom.2016.02.012>.
Imports: Brobdingnag (>= 1.2-5), mvnfast (>= 0.2.5), parallel (>=

Description: Unconstrained and constrained maximum likelihood estimation of Gaussian Mixture Vector Autoregressive (GMVAR)
model, quantile residual tests, graphical diagnostics, simulations, and forecasting.

Description: Unconstrained and constrained maximum likelihood estimation of structural and reduced form
Gaussian mixture vector autoregressive (GMVAR) model, quantile residual tests, graphical diagnostics,
simulations, forecasting, and estimation of generalized impulse response function.
Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2016) <doi:10.1016/j.jeconom.2016.02.012>,
Imports: Brobdingnag (>= 1.2-6), mvnfast (>= 0.2.5), parallel (>=

Imports: Brobdingnag (>= 1.2-4), mvnfast (>= 0.2.5), parallel (>=