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Today we want to pull back the curtain on how we built DartCannon and share our appreciation on all the projects that have helped us get here. The Core The foundational piece of DartCannon is our custom-build proprietary Monte Carlo simulation engine, Thompson. Under development in some form for over 8 years, Thompson is what enables us to iterate quickly and provide such high quality simulations at an affordable price point.


A few weeks late, but worth calling out that Directional 3.3 is out on CRAN. I had a small contribution which came out of my investigations into spherical densities.

I modified the respective posts to use the native Directional vmf.kerncontour rather than the previously unreleased modification I made to return the data.

Thanks to maintainer Michail Tsagris for accepting the patch and all his help.


Every week on DartCannon we give a rundown on the week including what we’ve written, are reading, and major imporvements. I won’t cross-post all of them, but will put them up every so often. Happy Friday! Here’s a rundown of this week in DartCannon What We Wrote Accepting an Estimate - DartCannon is about creating simulations of complex business problems, but once the simulation is done the work of getting buy in starts.


I recently realized that edgarWebR 1.0 was released a while ago without much fanfare. 1.0 is a major milestone for the library, bringing the full set of (initial) planned functionality along with some bonus features. Headline features: 100% coverage of SEC search tools. Parsing of submissions into component files and 10-x filings into items and parts. A dataset of SIC mappings What’s Next: Bugfixes - corner cases keep popping up that need fixing Parsing Improvements - I have some ideas about table handling that will help anyone interested in getting data out of older filings EDGAR Tools The EDGAR System provides a number of tools for filing and entity lookup and examination.


Last time we made contour maps of densities of points on a globe, now it is time to take another step and make heatmaps. We created all the data we needed when creating the contours, but heatmaps add new challenges of dealing with large amounts of raster and polygon data. Lets get to it. DISCLAIMER: While I know a thing or two, there’s a reasonable chance I got some things wrong or at very least there are certainly more efficient ways to go about things.




An online tool for making probability estimates of costs and schedules


A R Library for accessing and parsing SEC Filings


A R Library for reading pds3 content