Publications by Joseph Rickert
Norm Matloff: Mad(Data)Scientist
by Joseph Rickert Norman Matloff professor of computer science at UC Davis, and founding member of the UCD Dept. of Statistics has begun posting as Mad(Data)Scientist. (You may know Norm from his book, The Art of R Programming: NSP, 2011.) In his second post (out today) on the new R package, freqparcoord, that he wrote with Yinkang Xie, Nor...
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BARUG talks highlight R’s diverse applications
by Joseph Rickert The seven lightning talks presented to the Bay Area useR Group on Tuesday night were not only really interesting (in some cases downright entertaining) in their own right, but they also illustrated the diversity of R applications, and the extent to which R has become embedded in the corporate world. Two presentations with a whim...
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Quantitative Finance Applications in R – 5: an Introduction to Monte Carlo Simulation
by Daniel Hanson Last time, we looked at the four-parameter Generalized Lambda Distribution, as a method of incorporating skew and kurtosis into an estimated distribution of market returns, and capturing the typical fat tails that the normal distribution cannot. Having said that, however, the Normal distribution can be useful in constructing Mo...
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Diving into H2O
by Joseph Rickert One of the remarkable features of the R language is its adaptability. Motivated by R’s popularity and helped by R’s expressive power and transparency developers working on other platforms display what looks like inexhaustible creativity in providing seamless interfaces to software that complements R’s strengths. The H2O R ...
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R Helps With Employee Churn
by Joseph Rickert Pasha Roberts, Chief Scientist at Talent Analytics, is writing a series of articles on Employee Churn for the Predictive Analytics Times that comprise a really instructive and valuable example of using R to do some basic predictive modeling. So far, Pasha has published Employee Churn 201 in which he makes a case for the importan...
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Predict which shoppers will become repeat buyers
by James P. Peruvankal Kaggle just announced a competition to predict which shoppers will become repeat buyers. To aid with algorithmic development, they have provided complete, basket-level, pre-offer shopping history for a large set of shoppers who were targeted for an acquisition campaign. Files containing the incentives offered to each shoppe...
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Importing a log file with rxImport()
by Joseph Rickert Tuesday's post on a new Kaggle contest mentioned that Revolution Analytics offers a free trial for using Revolution R Enterprise in the Amazon cloud. One reason this might be of interest to contestants is the rxImport() function which reads delimited text data, fixed format text data, and with an appropriate ODBC driver, data st...
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R and the Collatz Conjecture: Part 2
by Seth Mottaghinejad, Analytic Consultant for Revolution Analytics In the last article, we showed two separate R implementations of the Collatz conjecture: 'nonvec_collatz' and 'vec_collatz', with the latter being more efficient than the former because of the way it takes advantage of vectorization in R. Let's once again take a look at 'vec_coll...
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R and Finance
by Joseph Rickert R/Finance 2014 is just about a week away. Over the past four or five years this has become my favorite conference. It is small (300 people this year), exceptionally well-run, and always offers an eclectic mix of theoretical mathematics, efficient, practical computing, industry best practices and trading “street smarts”. This...
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Plotly and rOpenSci: Make ggplots shareable and interactive.
By Matt Sundquist Plotly's Co-Founder Here at Plotly, we are on a mission to build a platform where data scientists can analyze data, create beautiful graphs and collaborate: like a GitHub for data, where you can share and find plots, data, and code. The benefits are: Plots (including ggplot2 plots) are interactive and drawn with D3 (try zooming...
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