From 29a54683c1858934a569f4975a6f8f33af032167 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Tomasz=20Wo=C5=BAniak?= Date: Wed, 17 Jul 2024 18:21:02 +1000 Subject: [PATCH] Update DESCRIPTION #12 --- DESCRIPTION | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 1c5edaa..ebceed0 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,11 +1,11 @@ Package: bsvarSIGNs Type: Package -Title: Bayesian Estimation of Structural Vector Autoregressive Models Identified by Sign, Zero, and Narrative Restrictions +Title: Bayesian Estimation of Structural Vector Autoregressions Identified by Sign, Zero, and Narrative Restrictions Version: 0.1.9000 Date: 2024-01-11 Authors@R: c(person("Xiaolei", "Wang", , "adamwang15@gmail.com", role = c("aut", "cre")),person("Tomasz", "Woźniak", , "wozniak.tom@pm.me", role = c("aut"), comment = c(ORCID = "0000-0003-2212-2378"))) Maintainer: Xiaolei Wang -Description: Implements efficient algorithms for the Bayesian estimation of Stuructural Vector Autoregressive models identified by sign, zero, and narrative restrictions following Rubio-Ramírez, Waggoner & Zha (2010) , Arias, Rubio-Ramírez, & Waggoner (2018) , and Antolín-Díaz & Rubio-Ramírez (2018) . +Description: Implements state-of-the-art algorithms for the Bayesian analysis of Structural Vector Autoregressions identified by sign, zero, and narrative restrictions. The core model is based on the flexible Vector Autoregression with the estimated hyper-parameters of the Minnesota prior as in Giannone, Lenza, Primiceri (2015) . The sign restrictions are implemented employing the methods outlined by Rubio-Ramírez, Waggoner & Zha (2010) , while identification through sign and zero restrictions follows the approach developed by Arias, Rubio-Ramírez, & Waggoner (2018) . Furthermore, our tool provides algorithms for identification via sign and narrative restrictions, in line with the methods introduced by Antolín-Díaz and Rubio-Ramírez (2018) . Users can also estimate a model with sign, zero, and narrative restrictions imposed at once. The package facilitates predictive and structural analyses using impulse responses, forecast error variance and historical decompositions, forecasting and conditional forecasting, as well as analyses of structural shocks and fitted values. All this is complemented by colourful plots, user-friendly summary functions, and comprehensive documentation. The `bsvarSIGNs` package is aligned regarding code structure, objects, and workflows with the R package 'bsvars' by Woźniak (2024) , and they constitute an integrated toolset. License: GPL (>= 3) Imports: R6, @@ -20,7 +20,7 @@ LinkingTo: Depends: R (>= 2.10), bsvars +Suggests: tinytest Encoding: UTF-8 LazyData: true RoxygenNote: 7.3.2 -Suggests: tinytest