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Tag: GitHub
reghdfe and R: The Joys of Standard Error Correction
Feed: R-bloggers. Author: An Accounting and Data Science Nerd's Corner. I am an applied economist and economists love Stata. Every time I work with somebody who uses Stata on panel models with fixed effects and clustered standard errors I am mildly confused by Stata’s ‘reghdfe’ function producing standard errors that differ from common R approaches like the {sandwich}, {plm} and {lfe} packages. Also, I recently had to update my {ExPanDaR} package to use the {plm} package as my favorite fixed effect package {lfe} was temporarily unavailable on CRAN. After doing that I decided that I finally want to understand what ... Read More
After the creation of ADAM: smooth v3.1.0
Feed: R-bloggers. Author: Ivan Svetunkov. [This article was first published on R – Open Forecasting, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Since the previous post on “The Creation of ADAM“, I had difficulties finding time to code anything, but I still managed to fix some bugs, implement a couple of features and make changes, important enough to call the next version of package smooth “3.1.0”. Here is what’s new: A new ... Read More
Deploy to Shinyapps.io from Github Actions
Feed: R-bloggers. Author: Roel M. Hogervorst. Last week I spend a few hours figuring out how to auto deploy a shiny app on 2 apps on shinyapps.io from github. You can see the result on this github repository. This github repository is connected to two shiny apps on shinyapps.io. Here is what I envisioned, every new commit to the main branch will be published to the main app. We could then lock down the main branch so that no one can directly commit to main. (this is the production version). Pull requests will be pushed to a testing version of ... Read More
The Time-Series Ecosystem

Feed: Featured Blog Posts - Data Science Central. Author: Luis. The Time-Series ecosystem Time-series analysis has been studied for more than a hundred years, however, the extraordinary growth of data available from numerous sources and more frequent growth of data alongside the growth of computer power (GPU & Multicore) makes the analysis of large-scale time-series data possible today in a way that was not previously practical. The use of time-series data has been traditionally linked to sectors where time is not just a metric but a primary axis, such as in finance, Industrial IoT, and energy. However, in the last ... Read More
Os Mutantes: an implausible naming system for SARS-CoV-2 mutants
Feed: R-bloggers. Author: quantixed. [This article was first published on Rstats – quantixed, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. The scientific response to the COVID-19 pandemic has been astounding. Aside from efforts to generate vaccines, the genomic surveillance of the virus has been truly remarkable. For example, the nextstrain project has sequence many SARS-CoV-2 genomes. In fact, the rapid identification of multiple new strains and mutations by diverse groups of scientists ... Read More
The Ethereum Virtual Machine (EVM)
Feed: Featured Blog Posts - Data Science Central. Author: Monika Sangwan. Vitalik Buterin (https://vitalik.ca) conceptualized Ethereum (https://ethereum.org) in November, 2013. The core idea proposed was the development of a Turing-complete language that allows the development of arbitrary programs (smart contracts) for blockchain and Decentralized Applications (DApps). This concept is in contrast to Bitcoin, where the scripting language is limited and only allows necessary operations. The EVM is a simple stack-based execution machine that runs bytecode instructions to transform the system state from one state to another. The EVM is a Turing-complete machine but is limited by the amount of gas ... Read More
Announcing public preview of Object-Level Security in Power BI
Feed: Microsoft Power BI Blog | Microsoft Power BI. Author: . Power BI Premium is built to meet the most demanding compliance, scale, and security requirements for enabling a data culture within your organization. Our recent announcements for large model support and XMLA endpoints enable fast query performance and solutions for your largest enterprise datasets; further empowering your teams to easily leverage large single source of truth datasets for intelligent decision-making. In this new environment, securing your datasets is not only prudent, but critical to successfully standardize BI within your enterprise. We‘re excited to announce that object level security (OLS) ... Read More
Random effects and penalized splines are the same thing
Feed: R-bloggers. Author: Higher Order Functions. [This article was first published on Higher Order Functions, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. For a long time, I’ve been curious about something. It is a truth I’ve seen casually dropped in textbooks, package documentation, and tweets: random effects and penalized smoothing splines are the same thing. It sounds so profound and enlightened. What does it mean? How are they the same? What deep ... Read More
Hazelcast C++ Client Thread Structure

Feed: Blog – Hazelcast. Author: Ihsan Demir. We have just released our newest version of Hazelcast C++ Client API. It has a lot of improvements and features compared to older releases and I would like to provide some insights into the thread structure of our client, including how it interacts with the user threads. IO Thread IO thread is one of the most important threads. It writes and reads client messages to and from the server. This thread is the busiest and on the critical path and should process IO bytes very fast. Therefore, on the reader side, it only ... Read More
Field Notes: Stopping an Automatically Started Database Instance with Amazon RDS

Feed: AWS Architecture Blog. Customers needing to keep an Amazon Relational Database Service (Amazon RDS) instance stopped for more than 7 days, look for ways to efficiently re-stop the database after being automatically started by Amazon RDS. If the database is started and there is no mechanism to stop it; customers start to pay for the instance’s hourly cost. Moreover, customers with database licensing agreements could incur penalties for running beyond their licensed cores/users. Stopping and starting a DB instance is faster than creating a DB snapshot, and then restoring the snapshot. However, if you plan to keep the Amazon ... Read More
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