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Tails are not memory. Memory is the dependence of the next increment on the previous one.
Distributions do not provide the slightest information about the presence/absence of memory - for that you need to consider conditional distributions or autocorrelation, which are essentially the same thing.
A simple illustration: I can shuffle any series of gradients (swap gradients randomly). The memory may or may not appear. But the distribution remains unchanged.
Citizens suffering from this problem, google and study the basics. It's ridiculous to read you.
Where is it written that tails are memory, I have read it several times, maybe I really wrote something like that, no I didn't, and where did you see it?
I suggest you reread Vladimir's posthttps://www.mql5.com/ru/forum/221552/page362#comment_7389227.
Inprobability theory andstatistics,the exponential distribution... isa probability distribution that describes the time between events ina Poisson point process.. It is a special caseof the gamma distribution. It is the continuous counterpart ofthe geometric distribution, and has the key property of beingmemoryless.
Source:https://en.wikipedia.org/wiki/Exponential_distribution
The Laplace distribution is a continuousprobability distribution... It is also sometimes calleda double exponential distribution... The difference between twoindependent equally distributed exponential random variables is defined by the Laplace distribution....The probability density function of the Laplace distribution also resembles thenormal distribution...Consequently, the Laplace distribution has denser tails than the normal distribution.
Source:https://en.wikipedia.org/wiki/Laplace_distribution
Inprobability theory andstatistics,the exponential distribution... isa probability distribution that describes the time between events ina Poisson point process.. It is a special caseof the gamma distribution. It is the continuous counterpart ofthe geometric distribution, and has the key property of beingmemoryless.
Source:https://en.wikipedia.org/wiki/Exponential_distribution
The Laplace distribution is a continuousprobability distribution... It is also sometimes calleda double exponential distribution... The difference between twoindependent equally distributed exponential random variables is defined by the Laplace distribution....The probability density function of the Laplace distribution also resembles thenormal distribution...Consequently, the Laplace distribution has denser tails than the normal distribution.
Source:https://en.wikipedia.org/wiki/Laplace_distribution
Well, look at that. Who would have thought?
Well, look at that. Who'd have thought?
Did I do something to offend or hurt you? I was just clarifying on thebas post where I took that nonsense.
And where I have it written that tails are memory, I've already read it several times, maybe I really wrote something like that, no I didn't, and where did you see it?
Well, if it's not written anywhere, then I'm glad I was wrong)
And your first link is really nonsense, they confuse distribution and process. The Russian version does not even write it. And in general, of course, it is better to refer to trusted textbooks, because anyone can write anything in the wiki)
Yes, gentlemen - the branch has turned into a complete disgrace. Taken over by fools.
Once again I ask the moderators to check everyone's education and employment records.
Until that happens, I refuse to communicate here. Anyone who wants one, write to me in person.
Yes, gentlemen - the branch has turned into a complete disgrace. Taken over by fools.
Once again I ask the moderators to check everyone's education and employment records.
Until that happens, I refuse to communicate here. Who needs it, write in person.
Alexander_K's third departure :-)
PS/ it's about time you got used to the fact that not everything in the world is perfect... on the other hand - check if the criticism and performances are subject to erlang's law? then you can brilliantly foresee it...
Yes, gentlemen - the branch has turned into a complete disgrace. Taken over by fools.
Once again I ask the moderators to check everyone's education and employment records.
Until that happens, I refuse to communicate here. Anyone who wants one, you'll have to write to me in person.
It's time to start the countdown.
For example, there are 10 days until the article is published
Alexander_K's third departure :-)
PS/ it's about time you got used to the fact that not everything in the world is perfect...on the other hand - check if criticism and performances are subject to Erlang's law ? then you can ingeniously anticipate it...
You won't believe it - for HALF OF YEARS I've only heard 1 smart tip here (he knows who and what I'm talking about) and 1 leading hint. Everything else is about nothing. What is all this for?