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I would think they have been getting royalties on episode reruns, since they were tracked down via a cue sheet, which has their names on it. Cue sheet is used by performing rights organizations to pay out royalties to performers. Given the story of the track's composition ("we need a song, you have four hours") my guess is that these folks have produced a large number of songs over the past 30 years that earn relatively small royalties per track. Add on top of that there are multiple tracks called "X-Files" just in this episode and I'd further guess there are plenty of songs that the musicians are getting paid for that they have forgotten over the years!

I still mention maintaining this site on my CV and LinkedIn - disappointingly I've never been asked about it in an interview. I suspect most of the people doing the interviewing these days are too young to remember it.

This is astonishing to me. I check back to see if this site is still up once every year or two just to have a smile. If you were sitting across from me in an interview I am quite sure I'd lose all pretense of professionalism and ask you about nothing else for the hour.

The SEC's response: "Nester explained that before staff can work on an issue that involves a company, they have to sell any holdings of stock in that firm. As a result, he said, there shouldn't be any surprise that a sale would precede the announcement of an enforcement action."

I don't know about anybody else, but this seems pretty plausible to me.

Thanks for your kind words. As somewhat of a novice myself, I found the lack of documented real-world use cases frustrating, so I'm super happy to see this kind of feedback! I hope this can help you down the road should you make a second attempt at Kalman filtering.

The likelihood itself is a single number, but the algorithm is maximizing the likelihood based on a vector of 993 parameters representing the quality of a seat. Each x,y coordinate represents a seat in the ballpark, and each seat is mapped to one of those 993 values. The heatmap evolves as the vector approaches maximum likelihood.