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 <adamwang15@gmail.com>
-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) <doi:10.1111/j.1467-937X.2009.00578.x>, Arias, Rubio-Ramírez, & Waggoner (2018) <doi:10.3982/ECTA14468>, and Antolín-Díaz & Rubio-Ramírez (2018) <doi:10.1257/aer.20161852>. 
+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) <doi:10.1162/REST_a_00483>. The sign restrictions are implemented employing the methods outlined by Rubio-Ramírez, Waggoner & Zha (2010) <doi:10.1111/j.1467-937X.2009.00578.x>, while identification through sign and zero restrictions follows the approach developed by Arias, Rubio-Ramírez, & Waggoner (2018) <doi:10.3982/ECTA14468>. 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) <doi:10.1257/aer.20161852>. 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) <doi:10.32614/CRAN.package.bsvars>, 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