Title: Bayesian Estimation of the GARCH(1,1) Model with Student's t Innovations
Description: This package provides the bayesGARCH function which performs the
Bayesian estimation of the GARCH(1,1) model with Student's t innovations.
Packaged: Tue Jun  3 13:10:19 2008; David Ardia

Title: Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations
Packaged: Wed Dec  3 22:08:02 2008; David Ardia

Title: Bayesian Estimation of the GARCH(1,1) Model with Student-t
Description: This package provides the bayesGARCH function which
performs the Bayesian estimation of the GARCH(1,1) model with
Packaged: Sun May 10 15:45:13 2009; David Ardia

Packaged: 2014-01-07 09:50:55 UTC; David Ardia

Authors@R: person("David", "Ardia", role = c("aut", "cre"), email = "david.ardia@fsa.ulaval.ca")
Description: Provides the bayesGARCH function which performs the
Packaged: 2015-12-15 01:50:24 UTC; David Ardia

Authors@R: person("David", "Ardia", role = c("aut", "cre", "cph"),
email = "david.ardia.ch@gmail.com", comment = c(ORCID = "0000-0003-2823-782X"))
Description: Provides the bayesGARCH() function which performs the
Bayesian estimation of the GARCH(1,1) model with Student's t innovations as described in Ardia (2008) <doi:10.1007/978-3-540-78657-3>.
Author: David Ardia [aut, cre, cph] (<https://orcid.org/0000-0003-2823-782X>)

Authors@R: person("David", "Ardia", role = c("aut", "cre"), email = "david.ardia.ch@gmail.com")

Title: Functions to implement Generalized Direct Sampling
Description: This package contains functions to help users implement
the Generalized Direct Sampling algorithm for Bayesian
hierarchical models (Braun and Damien, 2012).

Description: This package contains functions to help users implement the Generalized Direct Sampling algorithm for Bayesian hierarchical models (Braun and Damien, 2013). GDS is useful for sampling from posterior distributions for which there is a large number of conditionally independent heterogeneous units.
Depends: R (>= 3.0.2), Matrix (>= 1.1.0), compiler
Suggests: sparseHessianFD(>= 0.1.1), sparseMVN(>= 0.1.0), mvtnorm,