Friendly & Fast Input-Output Analysis
{fio}
(Friendly Input-Output) is a R package
designed for input-output analysis, emphasizing usability for Excel
users and performance. It includes an RStudio Addin and a
suite of functions for straightforward import of input-output tables
from Excel, either programmatically or directly from the clipboard.
The package is optimized for speed and efficiency. It leverages the R6 class for clean, memory-efficient object-oriented programming. Furthermore, all linear algebra computations are implemented in Rust to achieve highly optimized performance.
You can install the latest stable release of {fio} from CRAN with:
install.packages("fio")
install the latest tested but unreleased version from the main branch, use the precompiled binaries available on R-universe:
install.packages("fio", repos = c("https://albersonmiranda.r-universe.dev", "https://cloud.r-project.org"))
For the cutting-edge development version from the dev branch, you’ll need to compile it from source. This requires Rust to be installed on your system. You can install Rust using the following commands:
apt-get install cargo
dnf install cargo
brew install rustc
If you are just getting started with {fio}
, we recommend
you to read the vignettes
for a comprehensive overview of the package.
Calculate Leontief’s inverse from brazilian 2020 input-output matrix:
# load included dataset
<- fio::br_2020
iom_br
# calculate technical coefficients matrix
$compute_tech_coeff()
iom_br
# calculate Leontief's inverse
$compute_leontief_inverse() iom_br
And pronto! 🎉, you’re all good to carry on with your analysis. You
can evoke the Data Viewer to inspect the results with
iom_br$technical_coefficients_matrix |> View()
and
iom_br$leontief_inverse_matrix |> View()
.
Leontief’s inverse from brazilian 2020 input-output matrix
Other great tools for input-output analysis in R include: