Analytical Approaches for Organic Compound Properties

The report of Leistra on reported versus estimated boiling points and vapor pressures for pesticides provides an interesting case study in mathematical underpinnings for the phenomena investigated. Reports of chemical properties are available from many online databases such as ChemSpider, PubChem, and others. But these aggregate other sources of data to get chemical properties. In some cases, they are from a manufacturer. Of course, manufacturers often report values without a method or explanation of how it was determined. The article makes a number of assumptions, the most important of which is that reported values are based on experimental observations. That’s

Comments on RPN

I’ve started falling in love with reverse Polish notation (RPN) again. This mostly comes from using PCalc on my iPhone for a lot of calculations, lately. Like so many other kids, I grew up using the Texas Instruments, starting with the TI-82 and TI-85. In college, I “upgraded” to a TI-86, which I recently found in my basement, and it still works. It’s a testament to both the ruggedness of the Texas Instruments builds and the long-lasting durability of the Zilog Z-80, the silicon inside the case. This post won’t teach you how to use RPN, since there are plenty

Computational Methods for Numerical Analysis is Out Now!

My new book Computational Methods for Numerical Analysis with R came out today from Chapman & Hall/CRC Press. This book is a long-standing project of mine–originally started in 2001, and then using Octave as the base language. As the world didn’t need yet another book on doing numerical analysis in Octave, and therefore MATLAB, I eventually moved it to R. Computational Methods for Numerical Analysis with R is an overview of traditional numerical analysis topics presented using R. This guide shows how common functions from linear algebra, interpolation, numerical integration, optimization, and differential equations can be implemented in pure R

The Bumblebees are Back, and They’re Bad!

The virtual bumblebees are now available for download under an MIT license. The bees were kinda/sorta always available, but I have clarified the licensing. To celebrate, the Journal of Open Source Software has published a software abstract, “Virtual Bumblebees Artificial Life Simulation.” The Journal of Open Source Software (JOSS) is a great project that aims to be “a developer friendly journal for research software packages.” The overall idea is that research software should occasionally be able to stand alone as the outcome of a research project and in this case, it fit the bees perfectly. So I was quite happy

Data Science for Restaurant Inspections

At work, we just did a really neat set of predictive models for restaurant inspections. This is all based on the work Chicago did for the analysis. We kinda/sorta split into different groups and did analyses for three cities (with links to reports): Raleigh, North Carolina, Syracuse, New York, and Denver, Colorado. Together, these three reports show different approaches and analyses we used in the three different cities, along with discussion of how we applied the Chicago work. More information is available from our GitHub page: GitHub – iscoe/restaurant_inspections: Predicting violations for restaurant inspections restaurant_inspections – Predicting violations for restaurant

Announcing Computational Methods for Numerical Analysis

For about two years, I’ve been working on a book called Computational Methods for Numerical Analysis with R (CMNA), which will present an outline of numerical analysis topics with original (and simplified) implementations in R at a level appropriate for a graduate student or advanced undergraduate. Last night, I sent the latest draft to my editors, and I am quite pleased to say it should be heading into production, soon. The organizational structure of the text is based roughly on the organizational structure of MAPL 460 15-20 years ago: Introduction to Numerical Analysis Error Analysis Linear Equations Interpolation and Extrapolation