Thank you for using EviewsR!
To acknowledge our work, please cite the package:
PLAIN TEXT:
Mati S. (2020). EviewsR: A Seamless Integration of EViews and R. CRAN. https://CRAN.R-project.org/package=DynareR
Mati S., Civcir I., Abba S.I (2023). EviewsR: An R Package for Dynamic and Reproducible Research Using EViews, R, R Markdown and Quarto. The R Journal. doi:10.32614/RJ-2023-045, url: https://journal.r-project.org/articles/RJ-2023-045/
BIBTEX:
@Article{Mati2020,
title = {EviewsR: A Seamless Integration of EViews and R},
author = {Sagiru Mati},
year = {2020},
journal = {CRAN},
url = {https://CRAN.R-project.org/package=EviewsR},
}
@article{Mati2023,
author = {Mati, Sagiru and Civcir, Irfan and Abba, S. I.},
title = {EviewsR: An R Package for Dynamic and Reproducible Research Using EViews, R, R Markdown and Quarto},
journal = {The R Journal},
year = {2023},
note = {https://doi.org/10.32614/RJ-2023-045},
doi = {10.32614/RJ-2023-045},
volume = {15},
issue = {2},
issn = {2073-4859},
pages = {169-205},
}
For details, please consult our peer-review article 10.32614/RJ-2023-045
EviewsR is an R package that can run EViews program in R. It also
adds eviews
as a knit-engine to knitr
package,
so that users can embed EViews codes in R Markdown and Quarto
document.
While the ecosystem of R is great, it cannot run EViews codes, not talk of handling EViews objects dynamically and reproducibly. Even though, EViews can communicate with R, users still need to switch to type-setting application to embed the EViews outputs. Specifically:
I wish I could embed EViews codes in R Markdown or Quarto document
I wish I could dynamically import the EViews outputs (graphs, tables, equation and series) individually or at once into R, R Markdown or Quarto document without switching between these applications back and forth.
I wish I could use an R function in R, R Markdown or Quarto to:
graph EViews series objects.
graph an R dataframe using EViews.
import data from external sources such as csv
,
xlsx
as a new EViews workfile or into an existing
workfile.
create an EViews workfile from an R dataframe
save an EViews workfile page as a workfile or another file format.
execute EViews codes.
export an R dataframe as a new EViews workfile or to an existing EViews workfile.
save an EViews workfile as a workfile or another file format.
import EViews table object as kable
.
import EViews series objects as a dataframe or xts
object
import equation data members such as coefficients, standard errors, R2 and so on.
import EViews graph objects
import equation data members, graph, series and table objects all at once.
simulate a random walk process using EViews.
I wish I could do all of the above without opening the EViews!!!
EviewsR can be installed using the following commands in R.
install.packages("EviewsR")
OR
devtools::install_github("sagirumati/EviewsR")
To run the package successfully, you need to do one of the following
Don’t do anything if the name of EViews executable is one of the
following: EViews13_x64
, EViews13_x86
,
EViews12_x64
, EViews12_x86
,
EViews11_x64
, EViews11_x86
,
EViews10_x64
, EViews10_x86
,
EViews9_x64
, EViews9_x86
,
EViews10
. The package will find the executable
automatically.
Rename the Eviews executable to eviews
or one of the
names above.
Alternatively, you can use set_eviews_path()
function to set the path the EViews executable as follows:
set_eviews_path("C:/Program Files (x86)/EViews 10/EViews10.exe")
Please load the EviewsR package as follows:
```{r} .
library(EviewsR)
```
The package can work with base R, R Markdown or Quarto document.
After loading the package, a chunk for Eviews can be created by
supplying eviews
as the engine name in R Markdown or Quarto
document as shown below :
```eviews
'This program is created in R Markdown with the help of EviewsR package
wfcreate(page=EviewsRPage,wf=EviewsR_workfile) m 2000 2022
for %y EviewsR package page1 page2
pagecreate(page={%y}) EviewsR m 2000 2022
next
pageselect EviewsRPage
rndseed 123456
genr y=@cumsum(nrnd)
genr x=@cumsum(nrnd)
equation ols.ls y c x
freeze(OLSTable,mode=overwrite) ols
freeze(EviewsR_Plot,mode=overwrite) y.line
wfsave EviewsR_workfile
```
The above chunk creates an Eviews program with the chunk’s content,
then automatically open Eviews and run the program, which will create an
Eviews workfile with pages containing monthly sample from 2000 to 2022.
The program will also save an EViews workfile named
EviewsR_workfile
in the current directory.
The eviews
chunk automatically returns the outputs of
each equation object as a dataframe, accessible via
chunkLabel$pageName_equationName
. For example, The
R2 of the ols
equation object is
0.044951, which can be accessed using
`r EviewsR$eviewsrpage_ols$r2`
. We can obtain the table
object by chunkLabel$pageName_tableName
. Therefore,
EviewsR$eviewsrpage_olstable
will give us the
OLSTable
object as dataframe. Note the underscore
(_
) between the pageName
and
equationName
, and between the pageName
and
tableName
.
EviewsR$eviewsrpage_ols$r2
#> [1] 0.044951
EviewsR$eviewsrpage_ols$aic
#> [1] 4.310163
K = EviewsR$eviewsrpage_olstable[c(6, 8, 9), 1:5]
colnames(K) = NULL
knitr::kable(K, row.names = F, caption = "Selected cells of EViews table object")
Variable | Coefficient | Std. Error | t-Statistic | Prob. |
C | -0.301413 | 0.260956 | -1.155033 | 0.2491 |
X | -0.051410 | 0.014316 | -3.591137 | 0.0004 |
Table 7.1: Selected cells of EViews table object
The EViews series objects are also imported automatically as
dataframe (by default) or xts
objects (if we use chunk
option class="xts"
). They are accessed via
chunkLabel$pageName
.
head(EviewsR$eviewsrpage)
#> date x y
#> 1 2000-01-01 -0.06062345 0.34705763
#> 2 2000-02-01 0.40287977 0.04959103
#> 3 2000-03-01 1.13387526 0.56589164
#> 4 2000-04-01 1.34089330 1.35264827
#> 5 2000-05-01 0.54596099 1.05434874
#> 6 2000-06-01 0.96869514 0.61693341
The function create_object()
can be used to create an
Eviews object in the existing EViews workfile.
create_object(wf = "EviewsR_workfile", action = "equation", action_opt = "",
object_name = "eviews_equation", view_or_proc = "ls", options_list = "",
arg_list = "y ar(1)")
create_object(wf = "EviewsR_workfile", object_name = "x1", object_type = "series",
expression = "y^2")
EViews graphs can be included in R Markdown or Quarto document by
eviews_graph()
function.
To create graph from existing EViews series objects:
eviews_graph(wf = "EviewsR_workfile", page = "EviewsRPage", series = "x y",
mode = "overwrite", graph_procs = "setelem(1) lcolor(red) lwidth(4)",
graph_options = "m")
We can also create graph objects from an R dataframe
Data = data.frame(x = cumsum(rnorm(100)), y = cumsum(rnorm(100)))
eviews_graph(series = Data, group = TRUE, start_date = "1990Q4",
frequency = "Q")
To plot a scatter graph and histogram on the same frame:
eviews_graph(wf = "EviewsR_workfile", page = "EviewsRPage", series = "x y",
group = T, graph_command = "scat(ab=histogram) linefit()",
mode = "overwrite", graph_procs = "setelem(1) lcolor(green) lwidth(2)")
Data can be imported from external sources by
eviews_import()
function.
eviews_import(source_description = "eviews_import.csv", start_date = "1990",
frequency = "m", rename_string = "x ab", smpl_string = "1990m10 1992m10")
Alternatively, use the dataframe as the
source_description
.
eviews_import(source_description = Data, wf = "eviews_import1",
start_date = "1990", frequency = "m", rename_string = "x ab",
smpl_string = "1990m10 1992m10")
Similar to Eviews workfile, an Eviews page can be saved in various
formats by eviews_pagesave()
function.
eviews_pagesave(wf = "eviewsr_workfile", page = "EviewsRPage",
source_description = "pagesave.csv", drop_list = "y")
An Eviews workfile can be created using
eviews_wfcreate()
function in R.
eviews_wfcreate(wf = "eviews_wfcreate", page = "EviewsRPage",
frequency = "m", start_date = "1990", end_date = "2022")
Create a workfile from a dataframe
eviews_wfcreate(source_description = Data, wf = "eviews_wfcreate1",
page = "EviewsR_page", frequency = "m", start_date = "1990")
An EViews workfile can be saved various output formats using
eviews_wfsave()
in function in R.
eviews_wfsave(wf = "eviewsr_workfile", source_description = "wfsave.csv")
A set of Eviews commands can be executed with the help of
exec_commands()
function in R.
exec_commands(c("wfcreate(wf=exec_commands,page=eviewsPage) m 2000 2022"))
eviewsCommands = "pagecreate(page=eviewspage1) 7 2020 2022
for %page eviewspage eviewspage1
pageselect {%page}
genr y=@cumsum(nrnd)
genr x=@cumsum(nrnd)
equation ols.ls y c x
graph x_graph.line x
graph y_graph.area y
freeze(OLSTable,mode=overwrite) ols
next"
exec_commands(commands = eviewsCommands, wf = "exec_commands")
Use export_dataframe()
function to export dataframe
object to Eviews.
export_dataframe(wf = "export_dataframe", source_description = Data,
start_date = "1990", frequency = "m")
Import EViews equation data members into R, R Markdown or Quarto.
import_equation(wf = "EviewsR_workfile", page = "EviewsRPage",
equation = "OLS")
To access the imported equation in base R:
Import EViews graph objects(s) into R, R Markdown or Quarto.
import_graph(wf = "eviewsr_workfile")
To import only graphs that begin with x:
import_graph(wf = "exec_commands", graph = "x*")