Programming an estimation command in Stata: Writing a Java plugin

This post is the fourth in a series that illustrates how to plug code written in another language (like C, C++, or Java) into Stata. This technique is known as writing a plugin or as writing a dynamic-link library (DLL) for Stata.

In this post, I write a plugin in Java that implements the calculations performed by mymean_work() in mymean11.ado, discussed in Programming an estimation command in Stata: Preparing to write a plugin, and I assume that you are familiar with that material.

This post is analogous to Programming an estimation command in Stata: Writing a C plugin and to Programming an estimation command in Stata: Writing a C++ plugin. The differences are due to the plugin code being in Java instead of C or C++. I do not assume that you are familiar with the material in those posts, and much of that material is repeated here.

This is the 32nd post in the series Programming an estimation command in Stata. See Programming an estimation command in Stata: A map to posted entries for a map to all the posts in this series. Read more…

Programming an estimation command in Stata: Writing a C++ plugin

This post is the third in a series that illustrates how to plug code written in another language (like C, C++, or Java) into Stata. This technique is known as writing a plugin or as writing a dynamic-link library (DLL) for Stata.

In this post, I write a plugin in C++ that implements the calculations performed by mymean_work() in mymean11.ado, discussed in Programming an estimation command in Stata: Preparing to write a plugin. I assume that you are familiar with the material in that post.

This post is analogous to Programming an estimation command in Stata: Writing a C plugin. The differences are due to the plugin code being in C++ instead of C. I do not assume that you are familiar with the material in that post, and you will find much of it repeated here.

This is the 31st post in the series Programming an estimation command in Stata. I recommend that you start at the beginning. See Programming an estimation command in Stata: A map to posted entries for a map to all the posts in this series. Read more…

Programming an estimation command in Stata: Writing a C plugin

This post is the second in a series that illustrates how to plug code written in another language (like C, C++, or Java) into Stata. This technique is known as writing a plugin or as writing a dynamic-link library (DLL) for Stata.

In this post, I write a plugin in C that implements the calculations performed by mymean_work() in mymean11.ado, discussed in Programming an estimation command in Stata: Preparing to write a plugin. I assume that you are familiar with the material in that post.

This is the 30th post in the series Programming an estimation command in Stata. See Programming an estimation command in Stata: A map to posted entries for a map to all the posts in this series. Read more…

Programming an estimation command in Stata: Preparing to write a plugin

This post is the first in a series that illustrates how to plug code written in another language (like C, C++, or Java) into Stata. This technique is known as writing a plugin or as writing a dynamic-link library (DLL) for Stata.

Plugins can be written for any task, including data management, graphical analysis, or statistical estimation. Per the theme of this series, I discuss plugins for estimation commands.

In this post, I discuss the tradeoffs of writing a plugin, and I discuss a simple program whose calculations I will replace with plugins in subsequent posts.

This is the 29th post in the series Programming an estimation command in Stata. See Programming an estimation command in Stata: A map to posted entries for a map to all the posts in this series. Read more…

Importing Facebook data into Stata

In a previous post, we released a new command to import Twitter data into Stata. We have now added another new command, facebook2stata, that imports Facebook data. To install facebook2stata, type

net install https://www.stata.com/users/kcrow/facebook2stata, replace

Read more…

Categories: Data Management Tags: ,

Data management made easy

Data management and data cleaning are critically important steps in any data analysis. Many of us learned this lesson the hard way. Have you ever fit a model that includes age as a covariate and forgotten to convert the missing value codes of -99 to missing values? I have. Or maybe you overlooked a data entry error that resulted in an age of 354 that should have been 54. I’ve done that too. Careful data management and cleaning can help us avoid these kinds of embarrassing mistakes.

I recently recorded a series of data management videos for the Stata Youtube Channel. You can click on the links below to watch the videos. I included topics that I think are important, but the list is far from exhaustive. If you would like to see videos on additional topics, please leave your suggestion in the comments below.

Data management playlist

You can learn more about these topics and many others in the Data Management Reference Manual.

Nonlinear multilevel mixed-effects models

You have a model that is nonlinear in the parameters. Perhaps it is a model of tree growth and therefore asymptotes to a maximum value. Perhaps it is a model of serum concentrations of a drug that rise rapidly to a peak concentration and then decay exponentially. Easy enough, use nonlinear regression ([R] nl) to fit your model. But … what if you have repeated measures for each tree or repeated blood serum levels for each patient? You might want to account for the correlation within tree or patient. You might even believe that each tree has its own asymptotic growth. You need nonlinear mixed-effects models—also called nonlinear hierarchical models or nonlinear multilevel models. Read more…

Working with Java plugins (Part 2)

In my previous post, I talked about how to combine the Java library Twitter4J and Stata’s Java function Interface using Eclipse to create a helloWorld plugin. Now, I want to talk about how to call Twitter4j member functions to connect to Twitter REST API, return Twitter data, and load that data into Stata using the Stata SFI. Read more…

Categories: Programming Tags: , ,

Working with Java plugins (Part 1)

Introduction

Three months ago, I wrote about a new command, twitter2stata, that imports data from Twitter’s REST API into Stata. Today, I will show you the tools we used to develop this command. Writing this command from scratch solely in Mata or ado-code would have taken several months. Fortunately, we can significantly speed up our development using an existing Java library (Twitter4J) and Stata’s Java plugins. In this post, I will discuss the basic steps of how to leverage a Java library and the Stata Java API.

Java is the most popular programming language in the world, so there are many libraries to support your development. A quick Google search should tell you if a Java library exists for what you are trying to do; this is how we found the library Twitter4J. For the rest of this blog entry, a basic understanding of programming in Java is helpful, but not necessary. Read more…

Categories: Programming Tags: , ,

Importing WRDS data into Stata

Wharton Research Data Services (WRDS) is a leading research platform and business intelligence tool for 400+ corporate, academic, and government researchers. If your institution subscribes to WRDS, you can now easily access WRDS data remotely via Stata’s odbc command. For questions or subscription information click here. Read more…