On Thursday, February 28th at 7 pm UTC, as part of the Why R? Webinar series, we have the honour to host Dr gwynn stuydevant from the Harvard Business School. She will talk about vectorization in R, using different cases to illustrate it.
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- s. gwynn stuydevant, PhD
Dr. Gwynn Sturdevant is a post-doctoral fellow at Harvard Business School working on the Science of Science. She developed an extensive Shiny application to assist in balancing trials as a post-doctoral fellow with Ken Kleinman (University of Massachusetts, Amherst and Harvard University). Dr. Sturdevant has a PhD in Statistics from the University of Auckland, the birthplace of R, where she studied under Thomas Lumley (University of Auckland and University of Washington) and Ross Ihaka. She focused on finding long-term effects, after cessation of treatments, when noisy measurements cross a threshold in biometric data.
Efficient computation with R
Current innovations in coding have focused on ease of learning and reading. Unfortunately, a byproduct of these features is an increase in computation time for some coding. This talk will focus on vectorizing R code, or writing code that reduces computation times in some cases. The speaker will discuss 3 cases: bootstrapping to determine the population mean, finding eigenvectors for a matrix, and survival analysis with mismeasurement.