Blog Archives

R, Stan and Bayesian Statistics

June 23, 2016
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R, Stan and Bayesian Statistics

by Joseph Rickert Just about two and a half years ago I wrote about some resources for doing Bayesian statistics in R. Motivated by the tutorial Modern Bayesian Tools for Time Series Analysis by Harte and Weylandt that I attended at R/Finance last month, and the upcoming tutorial An Introduction to Bayesian Inference using R Interfaces to Stan that...

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Exploring Global Internet Performance Data Using R

June 21, 2016
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Exploring Global Internet Performance Data Using R

by Lourdes O. Montenegro Lourdes O. Montenegro is a PhD candidate at the Lee Kuan Yew School of Public Policy, National University of Singapore. Her research interests cover the intersection of applied data science, technology, economics and public policy. Many of us now find it hard to live without a good quality internet connection. As a result, there is...

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The R Packages of UseR! 2016

June 16, 2016
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The R Packages of UseR! 2016

by Joseph Rickert It is always a delight to discover a new and useful R package, and it is especially nice when the discovery comes with at context and testimonial to its effectiveness. It is also satisfying to be able to check in once in awhile and get an idea of what people think is hot, or current or...

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Using Microsoft R Server on a single machine for experiments with 600 million taxi rides.

June 14, 2016
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Using Microsoft R Server on a single machine for experiments with 600 million taxi rides.

by Dmitry Pechyoni, Microsoft Data Scientist The New York City taxi dataset is one of the largest publicly available datasets. It has about 1.1 billion taxi rides in New York City. Previously this dataset was explored and visualized in a number of blog posts, where the authors used various technologies (e.g., PostgreSQL and Apache Elastic Search). Moreoever, in a...

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R Consortium and User! 2016 News

June 9, 2016
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by Joseph Rickert IBM Joins the R Consortium This past Monday at the Spark Summit in San Francisco IBM announced that it had joined the R Consortium as a "Platinum" member. This is very good news with respect to the development and growth of the R language, the health of the R Community and the position of opensource software...

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Bayesian Optimization of Machine Learning Models

June 7, 2016
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Bayesian Optimization of Machine Learning Models

by Max Kuhn: Director, Nonclinical Statistics, Pfizer Many predictive and machine learning models have structural or tuning parameters that cannot be directly estimated from the data. For example, when using K-nearest neighbor model, there is no analytical estimator for K (the number of neighbors). Typically, resampling is used to get good performance estimates of the model for a given...

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Using caret to compare models

June 2, 2016
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Using caret to compare models

by Joseph Rickert The model table on the caret package website lists more that 200 variations of predictive analytics models that are available withing the caret framework. All of these models may be prepared, tuned, fit and evaluated with a common set of caret functions. All on its own, the table is an impressive testament to the utility and...

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Principal Components Regression in R: Part 3

May 31, 2016
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Principal Components Regression in R: Part 3

by John Mount Ph. D. Data Scientist at Win-Vector LLC In her series on principal components analysis for regression in R, Win-Vector LLC's Dr. Nina Zumel broke the demonstration down into the following pieces: Part 1: the proper preparation of data and use of principal components analysis (particularly for supervised learning or regression). Part 2: the introduction of y-aware...

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Some Impressions from R Finance 2016

May 27, 2016
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Some Impressions from R Finance 2016

by Joseph Rickert R / Finance 2016 lived up to expectations and provided the quality networking and learning experience that longtime participants have come to value. Eight years is a long time for a conference to keep its sparkle and pizzazz. But, the conference organizers and the UIC have managed to create a vibe that keeps people coming back....

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Principal Components Regression in R: Part 2

May 24, 2016
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Principal Components Regression in R: Part 2

by John Mount Ph. D. Data Scientist at Win-Vector LLC In part 2 of her series on Principal Components Regression Dr. Nina Zumel illustrates so-called y-aware techniques. These often neglected methods use the fact that for predictive modeling problems we know the dependent variable, outcome or y, so we can use this during data preparation in addition to using...

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