Publications by Joseph Rickert
Getting Started with Markov Chains
by Joseph Rickert There are number of R packages devoted to sophisticated applications of Markov chains. These include msm and SemiMarkov for fitting multistate models to panel data, mstate for survival analysis applications, TPmsm for estimating transition probabilities for 3-state progressive disease models, heemod for applying Markov models...
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Microsoft R Server available free to students with DreamSpark
by Joseph Rickert Over the last 6 years, thousands of students and faculty have downloaded Revolution R Enterprise (RRE) from Revolution Analytics for free, making it possible for them to do statistical modeling on large data sets with the same R language used by savvy statisticians and data scientists in business and industry. In addition to t...
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New Data Sources for R
by Joseph Rickert Over the past few months, a number of new CRAN packages have appeared that make it easier for R users to gain access to curated data. Most of these provide interfaces to a RESTful API written by the data publishers while a few just wrap the data set inside the package. Some of the new packages are only very simple, one function ...
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A gentle introduction to parallel computing in R
by John Mount Ph.D.Data Scientist at Win-Vector LLC Let's talk about the use and benefits of parallel computation in R. IBM's Blue Gene/P massively parallel supercomputer (Wikipedia). Parallel computing is a type of computation in which many calculations are carried out simultaneously.” Wikipedia quoting: Gottlieb, Allan; Almasi, George S. (1...
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Getting Started with Markov Chains: Part 2
by Joseph Rickert In a previous post, I showed some elementary properties of discrete time Markov Chains could be calculated, mostly with functions from the markovchain package. In this post, I would like to show a little bit more of the functionality available in that package by fitting a Markov Chain to some data. In this first block of code, I...
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Pipelining R and Python in Notebooks
by Micheleen HarrisMicrosoft Data Scientist As a Data Scientist, I refuse to choose between R and Python, the top contenders currently fighting for the title of top Data Science programming language. I am not going to argue about which is better or pit Python and R against each other. Rather, I'm simply going to suggest to play to the strengths o...
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R User Groups on GitHub
by Joseph Rickert Quite a few times over the past few years I have highlighted presentations posted by R user groups on their websites and recommended these sites as a source for interesting material, but I have never thought to see what the user groups were doing on GitHub. As you might expect, many people who make presentations at R user group ...
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Using Microsoft R Open with RStudio
by Joseph Rickert A frequent question that we get here at Microsoft about MRO (Microsoft R Open) is: can be used with RStudio? The short answer is absolutely yes! In fact, more than just being compatible, MRO is the perfect complement for the RStudio environment. MRO is a downstream distribution of open source R that supports multiple operating s...
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R User Groups in Poland
by Przemyslaw Biecek The first meeting of R users in Poland took place in Wroclaw in 2008. It was a one-day conference with 27 participants and 6 talks. Today, we have three large groups of R users in major Polish cities (according to meetup.com there is 640 users in SER – Warsaw, 235 in eRka – Cracow and 64 in PAZUR – Poznań). And there ...
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Getting Started with Microsoft SQL Server on Azure
by Joseph Rickert If you are an R user and work for an enterprise where Microsoft SQL server is important, it is extremely helpful to have easy access to SQL Server databases. Over the past year, we have run several posts on this topic including a comprehensive four part series from Microsoft's Gregory Vandenbrouck on using various flavors of SQL...
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