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 branches from Github, 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:
sudo apt install cargo
sudo dnf install cargo
brew install rust
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: