The Chinese Stata Conference takes place on 16 August 2020, in cooperation with the Wuhan University School of Economics and Management.
This conference will provide Stata users from across China and the world the opportunity to exchange ideas, experiences, and information on new applications of Stata. Representatives from StataCorp will attend. Anyone interested in using Stata is welcome.
|8:45–9:45||Fusion application of Stata and Python
Fusion application with Python is a new feature of Stata 16.
It allows Stata to run Python programs freely. I will
demonstrate the possibilities of expanding Stata and Python
through this series of examples.
|9:45–10:30||Link Stata to Chinese maps
I will introduce the principal methodology with which Stata reads
the geographic information from Baidu Maps and Gaode Maps, as well
as some map commands we developed.
... (Read more)
cngcode converts Chinese addresses to latitude and longitude. cnaddress converts latitude and longitude to Chinese iconic geographical locations. cntraveltime can calculate the traffic distance between two geographical locations (you can even choose different traffic modes). cnmapsearch can search for various geographical keywords such as subway stations, hospitals, cafes, barbecue stalls, etc., within a few kilometers of a given location. These commands are convenient for empirical research on geography and transportation and have broad application prospects in finance, economics, and sociology.
Zhongnan University of Economics and Law
|10:40–12:00||Using Stata 16's lasso features for prediction and inference
Lasso and elastic net are two popular machine-learning methods. In this
presentation, I discuss Stata 16's new lasso features for prediction and
... (Read more)
I will demonstrate how lasso-type techniques can be used for prediction with linear, binary, and count outcomes. I will then show why these methods are effective and how they work. The increasing availability of high-dimensional data and increasing interest in more realistic functional forms have sparked a renewed interest in automated methods for selecting the covariates to include in a model. I discuss the promises and perils of model selection and pay special attention to some new estimators that provide reliable inference after model selection.
|12:00–12:40||Visualization and modeling method of epidemic data of COVID-19
Since COVID-19 was found in 2019, the global spread has attracted extensive
attention. I will summarize basic methods for visualization of epidemic data
and explore the temporal and spatial characteristics of the global spread of
... (Read more)
I will then introduce a modeling method for forecasting the epidemic trend of COVID-19 so as to better adjust the policy of the epidemic prevention and control of the situation. Finally, I will summarize the matters needing attention in the epidemic data analysis of the situation.
The 2020 Chinese Stata Conference is jointly organized by Beijing Tianyan Rongzhi Software Co., Ltd. (TurnTech), an official reseller of Stata in China, and the Wuhan University School of Economics and Management.
View the proceedings of previous Stata Conferences and Users Group meetings.