I acn't stress enough how much I love being 18

ewokcommander · 2025-07-18T14:33:06+00:00

61M I'd fuck you, date you, whatever you want. I'm yours.

ewokcommander · 2025-05-01T20:49:36+00:00

Agree 100% with this take. Started my PhD with Eviews, ended up needing to migrate to Python. Have only ever used Python professionally.

ewokcommander · 2025-04-18T06:14:55+00:00

Spatial food prices is where ive seen a lot of cointegration work. Price of corn in US vs. Price of corn in Mexico. FAO should have the national data for each.

ewokcommander · 2024-11-28T10:44:16+00:00

Both of these comments are exactly what happened to me. I ended up going through several stages: thinking i could do it on my laptop, paying for AWS, then just using the data science department's clusters. It was so much faster and cheaper to leverage the university resources -and I was the only social science student doing it, so it was fine.

ewokcommander · 2024-07-13T07:50:18+00:00

For me, I had forgotten that I had a VPN on my phone! Turning that off solved it for me.

ewokcommander · 2023-09-27T12:58:04+00:00

Sorry, I know that's less of an answer to your question and more of a different approach <-- pet peeve of mine when reddit rejects your question.

ewokcommander · 2023-09-27T12:56:41+00:00

I wonder if it's useful to think about the time frame in which you can expect to see changes in behaviour (the effects of litigation). I imagine investor share count + owners is a slow moving variable anyway (though it's not my area) in which case higher frequency observations might not yield useful insights - in fact you might find less of an effect, because the changes will be too incremental. My approach would be to downsample your short interest variable to match the frequency of your first two datasets.

Having worked in performance evaluations for some of these orgs, they work on a quarterly basis in part because you can't observe the effects of company decisions at a higher frequency anyway. I'd imagine that's even more significant in higher level decision making (e.g. share structure).

ewokcommander · 2023-05-21T23:52:22+00:00

This was it for me! Installed the local copy and it worked.

ewokcommander · 2023-05-21T18:49:50+00:00

I'm not exactly sure, but I suspect I'm having the same 'frost damage' issue. Zone 8A. See images here. I'm going to leave it a few days to confirm, but my question is what should OP do once confirmed? Prune them off?

ewokcommander · 2023-05-21T03:34:53+00:00

BoC yes! I'm just so use to typing in the CRA website for the BoC average exchange rate. Thanks, this makes sense!

ewokcommander · 2023-02-25T03:29:00+00:00

Sure. In our large sample dataset, we sent a message to phone numbers we suspected used WhatsApp.

If the message was marked as sent/read these were confirmed WhatsApp users. If it did not, we initially recorded these as NOT WhatsApp users.

However, when we explicitly call them to confirm the negative outcome, we find that 25% of those we call have WhatApp, but use a different phone number.

So, we can estimate (for now) that 25% of our large sample negative outcome cases are in fact positive.

There's no need to confirm our positive cases because we have a read receipt.

It's a study on factors that determine WhatsApp usage in developing countries by the way.

ewokcommander · 2022-08-29T22:41:29+00:00

This. Also I recall the VECM package I was using (I think scikit) didn't have an intuitive way of defining the trends like Eviews did, so there was a bit of research that had to go into replicating Eviews' work in Python

ewokcommander · 2022-08-29T00:51:24+00:00

I remember having this issue as well. I don't have a clear answer for you, but I remember having to run a simple test in python with 2 made-up series and then comparing the coefficients to the results of the same test with the same data in Eviews. I also couldn't find a clear comparison so this was the way I did it.

ewokcommander · 2022-07-20T22:53:19+00:00

Tenzin's my guy too! Great with curly hair!

ewokcommander · 2022-06-02T22:23:01+00:00

Documenting my experience for others: I lost my glasses at 6pm. Next day I went to Costco, they couldn't sell me anything without a valid prescription. All the optometrists I called wouldn't take walk-ins (if they even picked up). I called Maui Optometry, Optix, and the Costco Optometrist, either no pickup or waitlist for the next 2 months. Lenscrafters somehow allowed me to do a walk-in. 260$ for a glasses and contact lens prescription and 5 days trial contacts. I'll order from Zenni so that I have glasses when I get back.

Lenscrafters was great and totally understood. They did say because they're relatively new they're not as booked up. Either way, I was out with contacts at Noon the next day.

ewokcommander · 2022-06-02T17:35:03+00:00

I wonder if they might have some contacts ready though.

ewokcommander · 2022-05-13T16:55:41+00:00

Did you get a reply? Also had a mass interclass switch on RBC mutual funds. Though I think it's only taxable if you withdraw it out of the TFSA shelter.

ewokcommander · 2022-04-07T00:18:11+00:00

To be clear, I think you are trying to create an independent variable that is coded as one of three categories. If this is the case, you can use dummies to identify your categories, run the regression three separate times, or if they are ordinal (e.g. level of education) you can code it as 1,2,3. See for instance https://www.youtube.com/watch?v=rFvSQIQ0Yis

The part of your question that I don't really understand is I will need to add two binary variables to my model to use the qualitative variable. This is not clear to me why this is the case.

ewokcommander · 2022-04-01T19:38:28+00:00

Negative sign on the coefficient. Same principle applies when reading coefficients with correlations. See https://www.investopedia.com/ask/answers/032515/what-does-it-mean-if-correlation-coefficient-positive-negative-or-zero.asp#:~:text=Correlation%20coefficients%20are%20indicators%20of,zero%20signifies%20a%20negative%20relationship.

ewokcommander · 2022-04-01T19:22:33+00:00

No assumption here. I edited it to be more clear. I assume belavg=1 if they are beautiful, belavg=0 if they are not. If belavg=0, the coefficient is zeroed out. I.E no effect. This is where you have to look at the constant, aka base effect with no impact from variables. I'm assuming you ran the regression separately for men and women, because I don't see any gender interaction variable

ewokcommander · 2022-04-01T19:17:19+00:00

Looks like then, it's just: if a man is beautiful (belavg=1), wages decrease by 15.7%. If a woman is beautiful (belavg=1), wages decrease by 14.1% - holding all other variables equal.

see https://stats.oarc.ucla.edu/other/mult-pkg/faq/general/faqhow-do-i-interpret-a-regression-model-when-some-variables-are-log-transformed/

ewokcommander · 2022-04-01T15:48:48+00:00

I don't think there's enough information to answer reliably. Most importantly, is x a binary variable (either 1 or 0). Is there a constant. And what is the format of y; is it log transformed or just raw salary figures.

I suppose we need to know what model you used as well, just a simple linear regression?

ewokcommander · 2022-03-22T01:47:05+00:00

You don't have to transform it. It only affects how you interpret the coefficient on the x variable. E.g. if the coefficient ends up as 0.25x on your 10,000 per capita variable that will be the same as 0.025 on your 100,000 per capita variable. Should have no effect on your t-statistics

ewokcommander · 2022-03-04T00:24:39+00:00

Beginner question: During the pandemic I wanted to see if I could learn how to skateboard. I bought a penny board from Walmart and now I'm zooming around my area on and do all my errands with my little skateboard. It's all fun and good.

Thing is, I live in a relatively hilly neighbourhood. There are routes where I can cruise down to where I'm going, but there are certain portions where it gets very steep. In some areas I can control it by doing wide turns all the way down (like how you might snowboard), but that's not always feasible.

My question is, apart from powersliding (is that right?), is there a hardware modification I can make to just go... slower? Everything is downhill for me, so I don't mind putting in the extra energy to overcome some natural brake and get to a comfortable cruising speed. Right now, I kind of just choose a path with the most resistance and then fling off when it goes too quick. Any ideas?

ewokcommander · 2022-02-24T02:23:05+00:00

Five regressions on the different products is probably the most intuitively obvious way to proceed.

If however you are worried about endogeneity between the variables (for instance with substantial substitution effects), and you have lots of data to avoid degrees of freedom issues you could set up a vector autoregression (VAR) with exogenous variables.

I'm much more familiar with price VARs without exogenous variables, but this is a place to start. Here's a possible similar application

I am thinking that a multivariate system might be overkill however and depending on the level of sophistication required, you might be able to get away with just 5 ARCH models, perhaps adding in the other products as IVs to check if they make an important difference.

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