Roberto Palloni has a nice series of posts on using R to acquire data from the web
I created a short .do file comparing several ways of estimating a two-period difference-in-differences model in Stata.
Code can be found on my Github page.
The Win-Vector LLC data science blog is starting a new series on using Spark and R to handle big data.
What we want to do with the “
Rand big data” series is:
Give a taste of some of the power of the
Share a “capabilities and readiness” checklist you should apply when evaluating infrastructure.
Start to publicly document
Describe some of the warts and how to work around them.
Share fun tricks and techniques that make working with
Sparkmuch easier and more effective.
Modeling Game of Thrones family network ties in R. Discusses important network measures like centrality, degree, closeness, betweenness centrality, diameter, transitivity, and others.
The University of North Carolina Population Center has a nice overview of ways to export Stata results to Word and other text processors.
About half of global paper is made from recycled fiber, making pulp and paper one of the few industries currently achieving some degree of circularity.
However, even this industry is facing supply constraints due to ever-growing paper demand. When demand for recycled fiber increases, either profit margins on recycled paper made from that fiber go down or the price of recycled paper goes up. Both results challenge the circular supply chain.
These dynamics suggest the difficulty of deploying circular supply chains in other industries. Initial promises of lower supply costs can be challenged by increased demand for recycled paper or by coordination costs in organizing the circular supply chain.
Example of linear regression using machine learning in R: https://datarvalue.blogspot.com/2017/05/machine-learning-linear-regression-full.html