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I'm going to be working on it while this post is up but I figured I'd ask your opinion of it.

Do you think that's a useful thing to know and how would you go about it?

Would you break it up into a spending array for each day or find some algorithm that can work with actual event times?

I'm going to be working on it while this post is up but I figured I'd ask your opinion of it. Do you think that's a useful thing to know and how would you go about it? Would you break it up into a spending array for each day or find some algorithm that can work with actual event times?

(post is archived)

[–] • 0 pt

I hope the series converge for you

[–] [deleted] • 0 pt

What is the purpose of doing this versus just using a spreadsheet and considering what's on it?

[–] • 0 pt

So I'm already doing some basic forcasting considering the average spending for a particular day of the month (for the last three months).

It's a lazy way of considering when bills are being auto-paid without thinking about every single bill.

But I'm realizing that my spending might have a stronger weekly component lately and in the future so I want to throw day of the week in there.

The question is how much to give to each effect so I need to see how strong the monthy component of my spending is compared to my weekly.

But then one might consider broadening it further and using all frequencies that come out of an fft.

I did find this which was interesting.

https://github.com/allanmcinnes/DEFT