From theory to practice - page 567
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Stationarity is just there. You're looking in the wrong place). Whether or not there is a distribution of G is of no concern to me.
What is stationarity? Where do you look?
There is no stationarity. Sometimes there may be the illusion of stationarity. But no more than that.
SO
I'm also talking about a trend - I'm defining it differently.
Hmmm... I have to say, I wasn't going to throw myself straight into neural networks...
On the contrary, it's from people like you, Yuri, that I expect to hear: "There is no Gaussian distribution, there is and will never be stationarity and Kolmogorov's theory (remember, I attached the book?) will never work". That would save a lot of time...
However, I heard this phrase already from Automat... Yes, yes, I remember...
Do you know the difference between a mathematical pendulum and a physical pendulum? I think you do.
The mathematical pendulum is not realizable in nature. But it is a good model. An ideal model, a kind of reference point, a base that allows you to evaluate properties, qualities, proximity to the ideal when considering a physical pendulum.
Do you understand what I am talking about?
So many opinions and not even on the trend issue have we come to an agreement. Let alone the other.
It's a binge about reversing pictures in Panteleon. Whoever needs it will translate them from Arabic and reverse them horizontally or vertically.
:)))) in Excel for the incremental modules of SUMM(A1:A1440) is 1 value, SUMM(A2:A1441) is 2, etc. There can't not be a normal distribution. You are looking for it, aren't you?
Prepare your pockets, dear Novaja, while I dust my purse...
Make a histogram! The data is in the file.
Histogram! The data is on file.
Is it just the amount of CLOSE M5?
Here:
This is clearly a convergent to normal distribution.
Such a thing, with a certain ACF, you can and should stick it into a neural network - it will literally take the cash out of it.
Is it just the amount of CLOSE M5?
Which file did you build from first or second?
And this is the variance of that process:
Obviously, xi-squared.
We're looking at a stationary process... It's a bit routine...
Get your wallets ready, gentlemen!!!
From which file did you build from the first or the second?
From the first one.