**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

The author of this package, **Sagiru Mati**, obtained his PhD in Economics from the Near East University, North Cyprus. He works at the Department of Economics, Yusuf Maitama Sule (Northwest) University, Kano, Nigeria. Please visit his website for more details.

Please follow his publications on **ORCID: 0000-0003-1413-3974**

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`

objectimport equation data members such as coefficients, standard errors,

*R*^{2}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}
#| label: fig-EviewsR
#| eval: true
#| fig.subcap: ["X graph","Y graph"]
#| fig.cap: "EViews graphs imported automatically by fig-EviewsR chunk"
'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 *R*^{2} 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*")`

Eviews tables can be imported as `kable`

object by `import_kable()`

function. Therefore, we can include the

```
import_kable(wf = "EViewsR_workfile", page = "EviewsRPage", table = "OLSTable",
format = "html", caption = "Selected cells of EViews table imported using import_kable() function",
range = "r7c1:r10c5", digits = 3)
```

Variable | Coefficient | Std. Error | t-Statistic | Prob. |
---|---|---|---|---|

C | -0.301 | 0.261 | -1.155 | 0.249 |

X | -0.051 | 0.014 | -3.591 | 0.000 |

Use `import_series()`

function to import data from EViews to R as a dataframe. The function creates a new environment `eviews`

, whose objects can be accessed via `eviews$pageName`

.

`import_series(wf = "eviewsr_workfile")`

To access the series in base R:

```
eviews$eviewspage %>%
head()
```

To import the series as an `xts`

object:

```
import_series(wf = "eviewsr_workfile", series = c("x", "y"),
class = "xts")
```

Import EViews table objects(s) into R, R Markdown or Quarto.

To import all table objects across all pages

`import_table(wf = "EviewsR_workfile")`

To import specific table objects, for example `OLSTable`

`import_table(wf = "EviewsR_workfile", table = "OLStable")`

To import table objects on specific pages

`import_table(wf = "EviewsR_workfile", page = " EviewsRPage")`

To access the table in base R (`eviews$pageName_tableName`

)

`eviews$eviewspage_olstable`

Import EViews equation data members, graph, series and table objects(s) into R, R Markdown or Quarto. This function is a blend of `import_equation()`

, `import_graph()`

, `import_series()`

and `import_table()`

functions.

To import all equation, graph, series and table objects across all pages

`import_workfile(wf = "EviewsR_workfile")`

To import specific objects

```
import_workfile(wf = "exec_commands", equation = "ols", graph = "x*",
series = "y*", table = "ols*")
```

To import objects on specific page(s)

`import_workfile(wf = "exec_commands", page = "eviewspage eviewspage1")`

To access the objects in base R:

```
eviews$eviewspage_ols # equation
# eviewspage-x_graph # graph saved in 'figure/' folder
eviews$eviewspage %>%
head() # series
eviews$eviewspage_olstable # table
```

A set of random walk series can be simulated in R using EViews engine, thanks to `rwalk()`

function.

```
rwalk(wf = "eviewsr_workfile", series = "X Y Z", page = "", rndseed = 12345,
frequency = "M", num_observations = 100, class = "xts")
xts::plot.xts(rwalk$xyz, type = "l", main = "")
ggplot2::autoplot(rwalk$xyz)
```

The demo files are included and can be accessed via `demo(package="EviewsR")`

```
demo(create_object())
demo(eviews_graph())
demo(eviews_import())
demo(eviews_pagesave())
demo(eviews_wfcreate())
demo(eviews_wfsave())
demo(exec_commands())
demo(export_dataframe())
demo(import_equation())
demo(import_graph())
demo(import_kable())
demo(import_series())
demo(import_table())
demo(import_workfile())
demo(rwalk())
demo(set_eviews_path())
```

Template for R Markdown is created. Go to `file->New File->R Markdown-> From Template->EviewsR`

.

You might be interested in the following packages:

DynareR: DynareR: Bringing the Power of Dynare to R, R Markdown, and Quarto

gretlR: A Seamless Integration of gretl and R.

URooTab: A Seamless Integration of gretl and R.

Please download the example files from Github.