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The goal of SVAA is is to provide an accessible and scalable framework for structural vector autoregressive analysis in R. While similar - and at this point more comprehensive - packages have long existed and been established within the R community (namely vars), SVAA is designed to... This guide will not only take you through the core functionality of SVAA, but also explain theory underlying the code. The package draws heavily on the text book Structural Vector Autoregressive Analysis by Lutz Kilian and Helmut Luethkepohl.


You can install SVAA from the Bank's package repository - Artifactory. In most cases R will automatically be linked to Artifactory, so you should be able to install SVAA in the same way you would install any other package:


If this does not work for you, please see here for guidance on accessing Artifactory.

Once installed you need to attach the package:



For detailed guidance on different topics and estimation methods covered by SVAA, you should consult the package vignettes. Simply type utils::browseVignettes() once you have completed the steps above.

pat-alt/SVAA documentation built on Feb. 19, 2021, 10:49 a.m.