cesarosum

If you're not shy of a few swear words, Nat's What I Reckon has some great recipes that are straightforward. Here's link to his bolognese - https://www.youtube.com/watch?v=Sw_Ze9zIafM

vim + vim-latex ;-)

Thanks for sharing this. I feel seen :)

Agreed, not knowing measure theory never stopped me from computing a conditional expectation. Some courses and books overemphasize rigor in probability and, while it obviously has its place, I've seen newcomers to the field become obsessed with doing everything via measure theory. Further to your point, volume two of Feller is pretty light on measure theory IIRC.

I do think that there's some merit in sticking with probability on discrete spaces for a while. Once you start dealing with continuous spaces, soon you're talking measure theory and you can wade deep into the technical details and miss some understanding of what's going on. I go back and forth on this as I think it's largely down to the reader to figure out what works for them, but I think probability is one of those fields where developing intuition early on is a must if you want to go further.

> it's simply a dumb idea.

Agreed. It's laughable. Dave Chappelle even parodied a similar concept (The Love Contract) on Chappelle's Show.

edit: the idea was actually called The Love Contract.

+1 for Andrews & Arnolds.

> Is Figure 8 an unconditional empirical CDF of inter-arrival times?

My understanding is that it's the inter-arrival times after some cleaning and resampling. If I've understood correctly, when they resampled the data, they did so uniformly between the neighbours of the points they omitted, which would actually make the data appear more like an exponential distribution.

> Especially considering its purpose. Maybe it would have been more accurate to say "there's a mixture of two Poissons: the bulk and the network disruption".

Could be. Could also follow a power law or a phase type distribution.

> But this isn't physics. We want to know how useful the approximation is, and whether there is a similarly tractable one with better predictive power.

It's worse, it's math :-) I take your point though, it all comes down to what you're trying to do. If inter-arrival times did follow an exponential distribution with parameter $\lambda$, then we'd have finite variance and I'd be pretty confident that I could build a performant predictive model. The presence of a heavy right tail makes me think otherwise.

It's definitely not a homogenous Poisson process, mainly because of the random changes to mining difficulty and propagation delays. There's a good paper here looking at block arrival times and fitting some different models - https://arxiv.org/pdf/1801.07447.pdf

To the programmer, developer or casual visitor looking at this and wondering whether it's worth the time and effort to dig into this, it is. Most of what's covered here can be understood with undergrad calculus, and will give you a solid basis for understanding and modelling random phenomena you may encounter in your studies, work or hobby.

Fun fact to get you started, Nakamoto suggested in the original Bitcoin paper that blocks would be added to the Bitcoin blockchain according to a homogenous Poisson process (spoiler alert: it's definitely not).

Regardless of whether the collection of the data was incidental or not, this is a huge breach of public trust given the assurances made by the Australian government.

For shame.

Disclaimer: I am one of the devs at Peergos.

You should definitely check out Peergos - https://peergos.org.

To point 3 - Protect what matters most - please do check out Peergos (https://peergos.org). We provide private and secure online storage that collects no metadata and is not dependent on DNS or TLS.

Disclaimer: I am one of the Peergos devs.

Disclaimer: I am one of the Peergos devs.

Yes, you should check out Peergos - https://peergos.org. Self-hosting details are on our GitHub page - https://github.com/Peergos/Peergos

I hear you. Here in the UK we have an unelected consultant to the Prime Minister who is pushing for a loosening of data privacy laws. The right to privacy is politicised to suit the agendas of politicians and big tech alike.

Long term, I do hope laws and regulation will catch up. I know some incredible people in the space and their work and commitment is inspiring. It's unsatisfying though to think that the effects will only be reactive and recourse provided after years of ongoing privacy invasion at mass scale. To me, that's where technology comes in and we should advocate and use products and solutions that respect our privacy (e.g. Qwant).

For what it's worth, I'm one of the developers of Peergos - https://peergos.org - a secure storage solution that puts user privacy and control of data first. We're currently in alpha and looking for users to test it out and give feedback. If it interests you at all, I would really appreciate your views on the product and what we're trying to create.

Equating privacy and privilege is not helpful. It is true that the privileged in our society wield more capability to enact protect and enact change for themselves and others in society, and privacy may not be top of mind when ranked against more immediate concerns such as those you have listed, but that doesn't change the fact that privacy is a universal human right and essential to our dignity and the functioning of society. It is something to be valued and upheld for everyone, not dismissed as a concern for the privileged alone.

+1 for mentioning Carissa Véliz. Her podcasts are really good as well - https://www.carissaveliz.com/podcasts.

It saddens me to read this sentiment. I agree there is a huge uphill battle to fight here to change the current situation, but there are a) plenty of people who value their privacy and are willing to make changes to the products and technologies they use in order to preserve their rights, and b) developers creating technology, tools and products that will protect your online privacy.