Sagiru Mati (PhD)
gretlR is an R package that can run gretl program from R, R Markdown and Quarto.
gretlR can be installed using the following commands in R.
install.packages("gretlR")
OR
# devtools::install_github('sagirumati/gretlR')
install.packages("gretlR", repos = c('https://sagirumati.r-universe.dev', 'https://cloud.r-project.org'))
Please load the gretlR package as follows:
```{r gretlR}
library(gretlR)
```
Then create a chunk for gretl as shown below:
```{gretl gretlR,eval=T,echo=T,comment=NULL}
nulldata 500
set seed 13
gretl1 = normal()
gretl2 = normal()
setobs 12 1980:01 --time-series
gnuplot gretl1 --time-series --with-lines --output="line.png"
gnuplot gretl2 gretl1 --output="scatter.png"
ols gretl1 const gretl2
modeltab add
tabprint --output="olsTAble.Rmd"
tabprint --output="olsTable.tex"
tabprint --output="olsTAble.csv"
eqnprint --output="olsEquation.tex"
```
The above chunk creates a gretl program with the chunk’s content, then
automatically run the gretl script, which will save gretl outputs in the
new folder gretlR created in the current working directory.
We can dynamically and reproducibly fetch the gretl graph object we
created with the gretl chunk using the following R chunk:
For the scatter graph:
include_graph(chunk = "gretlR",graph = "scatter.png")
or the line graph:
include_graph(chunk = "gretlR",graph = "line.png")
we can also include the equation of the OLS generated by the gretl
chunk and save as olsEquation.tex.
If the output is pdf, one can use the raw LaTeX codes as follows:
\input{gretlr/gretlR/olsEquation.tex}
Or use include_tex function to include the equation as shown below:
include_tex(chunk = "gretlR",tex = "olsEquation")
include_tex(chunk = "gretlR",tex = "olsTAble",start = 7,end = 24)
The OLS table output is saved by the gretl chunk as olsTable.Rmd.
The entire OLS table output can included as child document as follows:
```{r child, child='gretlr/gretlR/olsTable.Rmd'}
```
The gretl chunk also saves the OSL table as olsTable.csv. The
import_kable function can be used to import it as a table. further
customisation can be done with kableExtra package.
import_kable(chunk = "gretlR",file = "olsTAble.csv",caption="Table generated from gretl
chunk", start=3,end=7,digits=2) |>
kableExtra::kable_styling(latex_options = c("basic","hold_position","scale_down")) |>
kableExtra::row_spec(0,bold=T)
This function writes gretl file.
code=r'(nulldata 500
set seed 13
gretl1 = normal()
gretl2 = normal()
setobs 12 1980:01 --time-series
gnuplot gretl1 --time-series --with-lines --output="line.png"
gnuplot gretl2 gretl1 --output="scatter.png"
)'
write_inp(code,path="gretlCodes")
This function executes existing gretl files.
code=r'(nulldata 500
set seed 13
gretl1 = normal()
gretl2 = normal()
setobs 12 1980:01 --time-series
gnuplot gretl1 --time-series --with-lines --output="line.png"
gnuplot gretl2 gretl1 --output="scatter.png"
)'
write_inp(code,path="SomeFolder/gretlCodes")
exec_inp("someFolder/gretlCodes")
This function creates gretlfile from R object or a set of character
strings and executes it. It is a combination of write_inp and
exec_inp functions.
code=r'(nulldata 500
set seed 13
gretl1 = normal()
gretl2 = normal()
setobs 12 1980:01 --time-series
gnuplot gretl1 --time-series --with-lines --output="line.png"
gnuplot gretl2 gretl1 --output="scatter.png"
)'
exec_gretl(code)
Demo can be accessed via demo(package="gretlR").
demo(exec_inp)
demo(write_inp)
demo(exec_gretl)
The R Markdown template for the gretlR can be accessed via
file -> New File -> R Markdown -> From Template -> gretlR
Similar packages include EviewsR (Mati 2022b, 2020b,Mati, Civcir, and Abba 2023), DynareR (Mati 2020a, 2022a), and URooTab (Mati 2023b, 2023a)
For further details, consult Mati 2020c and 2022c.
Please download a set of example files from Github.
Mati, Sagiru. 2020a. “DynareR: Bringing the Power of Dynare to R, R Markdown, and Quarto.” CRAN. https://CRAN.R-project.org/package=DynareR.
———. 2020b. EviewsR: A Seamless Integration of EViews and R. https://CRAN.R-project.org/package=EviewsR.
———. 2020c. gretlR: A Seamless Integration of Gretl and R. https://CRAN.R-project.org/package=gretlR.
———. 2021. “Do as Your Neighbours Do? Assessing the Impact of Lockdown and Reopening on the Active COVID-19 Cases in Nigeria.” Social Science &Amp; Medicine 270 (February): 113645. https://doi.org/10.1016/j.socscimed.2020.113645.
———. 2022a. “Package ‘DynareR’.” https://cran.r-project.org/web/packages/DynareR/DynareR.pdf.
———. 2022b. “Package ‘EviewsR’.” https://cran.r-project.org/web/packages/EviewsR/EviewsR.pdf.
———. 2022c. “Package ‘gretlR’.” https://cran.r-project.org/web/packages/gretlR/gretlR.pdf.
———. 2023a. “Package ‘URooTab’.” https://cran.r-project.org/web/packages/URooTab/URooTab.pdf.
———. 2023b. URooTab: Tabular Reporting of EViews Unit Root Tests. https://github.com/sagirumati/URooTab.
Mati, Sagiru, Irfan Civcir, and S. I. Abba. 2023. “EviewsR: An r Package for Dynamic and Reproducible Research Using EViews, r, r Markdown and Quarto.” The R Journal 15 (2): 169–205. https://doi.org/10.32614/rj-2023-045.
Mati, Sagiru, Irfan Civcir, and Hüseyin Ozdeser. 2019. “ECOWAS COMMON CURRENCY: HOW PREPARED ARE ITS MEMBERS?” Investigación Económica 78 (308): 89. https://doi.org/10.22201/fe.01851667p.2019.308.69625.
Mati, Sagiru, Irfan Civcir, and Hüseyin Özdeşer. 2023. “ECOWAS Common Currency, a Mirage or Possibility?” Panoeconomicus 70 (2): 239–60. https://doi.org/10.2298/pan191119015m.
Mati, Sagiru, Magdalena Radulescu, Najia Saqib, Ahmed Samour, Goran Yousif Ismael, and Nazifi Aliyu. 2023. “Incorporating Russo-Ukrainian War in Brent Crude Oil Price Forecasting: A Comparative Analysis of ARIMA, TARMA and ENNReg Models.” Heliyon 9 (11): e21439. https://doi.org/10.1016/j.heliyon.2023.e21439.