Jeremiah

I already know where you stand, Michael.

Still not interested. I don't even read your post, I just kind of skim over them. You know, like you were doing to me.

You don't "guess" a prior. Priors have to be justified. If you don't know you use an uninformative prior.

The simple truth of this is, if I walked up to you on the street and handed you one envelope and said one of these has twice as much as the other, you...

I have been very clear on my position, and this is why I stonewalled you. It was clear to me that you were not reading my posts. You kept "disagreeing...

Random selection, which means equal probability, mitigates observational bias by treating each n in a population the same. This helps maximize the inf...

check the definition of a random sample. It has a very interesting definition in this context, which I actually already posted in this thread.

Ask yourself why they generally are using equiprobability as a prior when they are uninformed. There is a reason why, why random samples use equiproba...

the philosophy in Bayesian statistics of using an uninformative prior.

I'll tell you what next time I do a class project I won't use a random sampling method and we'll see if I get an F or an A. Good thing I am learning h...

Over the long run an equiprobability as a prior has the least amount of drag. Unless you can justify using a weighted selection method it is the best ...

I should note a credit to the philosophers, I have found, after crossing over to science, that the science types do seem to have problems with the why...

If you don't use a random sampling method your event could become skewed by observational bias. I am sure there are cases to use weighted selection me...

Equiprobability is unbiased.

The simplest explanation is that our gain/loss is either x or-x.

If you introduce a known distribution then you are making assumptions about the distribution. Classical or Bayesian, it does not matter, that is true ...

The whole distribution thing is faulty. I agree in the strictness sense of the definition there is an unknown distribution, but as far was we know it ...

I picked up my contempt for philosophy from these forums many years ago. I was a member of the old forums. Which is why you need to stop and ask yours...

As I said many, many times algreba is the correct tool to use here. Not Baysian or Classical statistics, but simple algreba. Simply because I talk abo...

I really do not care about this Classical vs Baysian nonsense you all have going on in these forums. That mind set didn't even exist to me before you ...

We went from being totally uninformed at the start of the thread to the knowledge gained after thousands of iterations with predefined conditions neve...

It is an interesting idea in terms of exploring unknown distributions; however, no one has actually justified this approach with respects to the OP. P...

A "switching strategy" is essentially machine learning. It is also out of scope of the OP, there is no guarantee such methods are applicable.

The best way to sovle this is still the simple algreba, it introduces no new assumptions. However, if you are going to simulate this it should be done...

It needs a simulation with a distribution but gives no new information of the distribution. Perhaps by scrambling the possible outcome than assigning ...

A "switch strategy" is just a way to approximate the distribution through iterations. Or the transformed distribution.

I choose 10 billion.

I already ran my own simulations, Michael, and the idea that if this was a game you'd get many turns to learn the range is very unrealistic. This is w...

Even if this was a game show, they are not going to give you 20,000 goes to figure out their range. That makes no sense. This is what I mean by being ...

Don't get me wrong, Michael, I found your linked article here an interesting read, but it moves beyond the scope of the problem in the OP, and all the...

Basing it on "previous games" is an assumption. That information was never in the OP.

No, I used the same scale in my code. It is this: if ( 0 == max_2x || choice <= max_2x / 2 ) { switch <- switch + other } # Otherwise increase the swi...

If you are doing it based on the your X, X/2 sample space, you'll get your expected gain. I have no doubt about that. The math already proves that. To...

If you use a distribution you are making assumptions not included in the OP. I pointed this out before. One thing we can be sure of from the OP is tha...

I like using simulations for empirical investigation; however, you and I, deeply disagree on the underlying assumptions and the code will reflect that...

Thank you, sorry for getting riled, I just hate going over someone else's code without notes.

You still need to notate your code. Especially on forums like these. I don't know why you don't do that. It almost makes it seem like you are trying t...

I only read R.

As I pointed out the thread is just going in circles.

I already commented on the assumptions that follow the use of distributions earlier in this thread. So basically we are back to once more modeling a p...

They are making a lot of assumptions. Conditions and information not included in the OP.

You should be willing to empirically justify your theory.

No amount of "math" will ever change the actual contents of the envelopes. Some of you are just pushing numbers around on the page, but math is not ma...

Like making a bunch of assumptions based on Y.

This is why I became disillusioned with philosophy. I wanted real answers, not made up ones

In any science you should repeatedly stop and ask yourself, "Is this correct?"

It absolutely makes sense to ask if it is correct, and that should be the first question you ask yourself whenever you model something.

I will not further debate such specifics.

I read that part. In fact I read it several times.

I am already convinced my approach is correct, Michael. I have no doubt about it, and I no longer care about arguing or proving that point. You can in...