Publications by Joseph Rickert
Forecasting By Combining Expert Opinion
by Michael Helbraun Michael is member of Revolution Analytics Sales Support team. In the following post, he shows how to synthesize a probability distribution from the opinion of multiple experts: an excellent way to construct a Bayesian prior. There are lots of different ways to forecast. Depending on whether there’s historical data, trend, ...
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Quantitative Finance Applications in R – 2
by Daniel Hanson QA Data Scientist, Revolution Analytics Some Applications of the xts Time Series Package In our previous discussion, we looked at accessing financial data using the quantmod and Quandl R packages. As noted there, the data series returned by quantmod comes in the form of an xts time series object, and Quandl provides a paramete...
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Topological Data Analysis with R
by Joseph Rickert When I was in graduate school in the mid '70s Mathematics departments were still under the spell of abstraction for its own sake. At that time, Algebraic Topology which uses concepts from Abstract Algebra to study topological spaces was a major gateway to the realm of abstraction. On my first visit, it was not at all clear that ...
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Book review: "Doing Data Science" by Rachel Schutt and Cathy O’Neil
by Joseph Rickert Every once in a while a single book comes to crystallize a new discipline. If books still have this power in the era of electronic media, “Doing Data Science, Straight Talk from the Frontline” by Rachel Schutt and Cathy O’Neil: O'Reilly, 2013 might just be the book that defines data science. “Doing Data Science”, which...
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Quantitative Finance Applications in R – 3: Plotting xts Time Series
by Daniel Hanson, QA Data Scientist, Revolution Analytics Introduction and Data Setup Last time, we included a couple of examples of plotting a single xts time series using the plot(.) function (ie, said function included in the xts package). Today, we’ll look at some quick and easy methods for plotting overlays of multiple xts time series i...
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A First Look at rxDForest()
by Joseph RIckert Last July, I blogged about rxDTree() the RevoScaleR function for building classification and regression trees on very large data sets. As I explaned then, this function is an implementation of the algorithm introduced by Ben-Haim and Yom-Tov in their 2010 paper that builds trees on histograms of data and not on the raw data i...
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Revolution Analytics announces $999 site licenses for universities and public service organizations
by Joseph Rickert Revolution Analytics is announcing three new programs today that we hope will be modest but positive contributions to data science education and public service analytics. The first new program, the Academic Institution Program (AIP) enables colleges, universities and other educational institutions to obtain a site license for Re...
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R and the Weather
by Joseph Rickert The weather is on everybody's mind these days: too much ice and snow east of the Rockies and no rain to speak fo in California. Ram Narasimhan has made it a little easier for R users to keep track of what's going on and also get a historical perspective. His new R package weatherData makes it easy to down load weather data from...
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Revolution R Enterprise in the Amazon Cloud
by Oliver Vagner, Cloud Solutions Lead Architect at Revolution Analytics Today, I am pleased to announce our new offering in the Amazon Web Services Big Data Marketplace – Revolution R Enterprise 7 for AWS. Of course, if you follow this blog, then you are quite familiar with Revolution R Enterprise (RRE) and what it brings to the table with its...
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3D Plots in R
by Joseph Rickert Recently, I was trying to remember how to make a 3D scatter plot in R when it occurred to me that the documentation on how to do this is scattered all over the place. Hence, this short organizational note that you may find useful. First of all, for the benefit of newcomers, I should mention that R has three distinct graphics sy...
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