RStata | [R package]: A R-Stata interface | Development Tools library

by lbraglia R Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | RStata Summary

RStata is a R library typically used in Utilities, Development Tools applications. RStata has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

A simple R -> Stata interface allowing the user to:.

Support

Quality

Security

License

Reuse

Support

RStata has a low active ecosystem.

It has 95 star(s) with 37 fork(s). There are 8 watchers for this library.

It had no major release in the last 6 months.

There are 12 open issues and 11 have been closed. On average issues are closed in 106 days. There are 5 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of RStata is current.

Quality

RStata has 0 bugs and 0 code smells.

Security

RStata has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

RStata code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

RStata does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

RStata releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

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RStata Key Features

No Key Features are available at this moment for RStata.

RStata Examples and Code Snippets

No Code Snippets are available at this moment for RStata.

Community Discussions

Trending Discussions on RStata

How to capture Rstata package output for subsequent processing in R

Stata formula in R without Stata installation

Issue with calculating marginal effects for an ordered logit model in R with ocME

QUESTION

How to capture Rstata package output for subsequent processing in R

Asked 2019-Sep-11 at 17:26

I run the following code:

...

ANSWER

Answered 2019-Sep-11 at 09:10

The only way you can do this with RStata, is by extracting the results and saving them as variables in a modified dataset, which you then send back to R.

The following toy example returns to object a the coefficients from a linear regression:

Source https://stackoverflow.com/questions/57881623

QUESTION

Stata formula in R without Stata installation

Asked 2019-Jan-15 at 07:41

Is it possible to translate a Stata formula into R without having a Stata installation on your PC?

My question is just the above, but let me give you some background how it came to me: I have the following Stata formula

...

ANSWER

Answered 2019-Jan-15 at 04:00

This is technically Mata, not Stata, code. Mata is the newer of Stata's two matrix programming languages. You invoke it by typing mata in the Stata command window.

Without knowing more about M and p, it is hard to give concrete advice. You can find Mata manuals online as pdf files. See the op_colon entry here and the c_conformability entry here.

Colon operators perform element-by-element operations, so M :/ p divides each element of M by the corresponding element of p if the two are the same size.

If they are not the same size, something similar happens (say divide by the same row or column vector), which works as long as the dimensions of the vectors is suitable.

One that is done, you calculate the transpose of that twice divided matrix, and matrix multiply by the original M.

Here are some mata examples:

Source https://stackoverflow.com/questions/54190560

QUESTION

Issue with calculating marginal effects for an ordered logit model in R with ocME

Asked 2018-Dec-30 at 20:43

I am attempting to estimate an ordered logit model incl. the marginal effects in R through following the code from this tutorial. I am using polr from the MASS package to estimate the model and ocME from the erer package to attempt to calculate the marginal effects.

Estimating the model is no problem.

...

ANSWER

Answered 2018-Dec-05 at 13:20

Your model has only one explanatory variable (mean_sentiment) and this seems to be a problem for ocME. Try for example to add a second variable to the model:

Source https://stackoverflow.com/questions/53631777

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