Dependency statistics in quotes (information theory, correlation and other feature selection methods) - page 60
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faa1947:
What does random drift wandering mean, or on what basis or to what is this concept introduced?
That's me researching the article ;)
Don't pester the man. The forecast error for each successive bar adds up. It is very difficult to get an acceptable forecast error even for one bar.
You have already been shown the possibilities of forecasting. With acceptable error. You have shown screenshots of different prediction durations. And you are again talking about the effect of winter crops on milk yields the year before.
Why am I hanging on to.... It's just that I have a huge number of known working methods in front of me that I'll never be able to master.
And about the chip. A person takes a tool (a chip) and for some unknown reason knows how to use it to enrich himself. The problem is that you can spend years and then find out that you either can't learn this trick (not given), or it was a fake. And too bad that in the beginning there was proof that this is not a tool, and do not know what. But greed overcame thoughts of chiromancy.
So I say:
(a) what is the error of prediction?
(b) can this prediction error be trusted?
(c) why will the answers to the first two questions be valid in the future?
No answer to these questions - everyone, off the screw and gazing with delight at a depot with 200 times growth in three months.
Which forecast are you referring to? To or from where?
What is meant by crowd?
Is there a justification of the crowd influence on the quote or is there a crowd influence in the quote? In every quote or only in some quotes?
I don't even remember when I wrote.
Thank you. Reading.
Crowd influence is from the books. But I think it's right. A lot of small purchases.
I'm not interested in that. The method is different, standard.
The following idea has already been stated here.
We take a quotient. We decompose it into two components: analytical and residual. The principle of "reversibility" is important, i.e. if we add the decomposition, we get the original quotient. Always. At all points. I.e. we do not lose a pip of initial data.
The analytical component to the piggy bank. Let us begin to deal with the remainder. If the form of the analytical curve is successful, then the residue is well analyzed by the methods of statistics. Approximately so.
Hmm, why the rules on Onyx and ask questions here?
ZS: I'm already used to this forum - here some members can scatter their bright ideas on a dozen topics, collects by search together, but to collect your posts around runet ..., oops, wrote a nickname ..., but he too sends somewhere to spider, etc. to collect his bright ideas, a few hours ago I asked him to sketch links in this thread, no response yet saw
Which forecast are you referring to? To where or to where?
Don't pester the man. The forecast error for each successive bar adds up. It is very difficult to get an acceptable forecast error even for one bar.
Mathemat:
При каком распределении ошибок?
Oh, and you say you don't understand. You've been leading me around by the nose for a year.
If it's a good model, the mistakes will be normal. But that's unlikely. Even with a one-step-ahead forecast, the headaches are over the top.
Well, if a lot of savvy ones don't formalise, then it's a gut feeling))
In this regard, the notion of "gut feeling" needs clarification.
I don't even remember when I wrote.
Thank you. Reading.
Crowd influence is from the books. But I think it's the right thing to do. A lot of small purchases.
I'm not interested in that. The method is different, standard.
The following idea has already been stated here.
We take a quotient. We decompose it into two components: analytical and residual. The principle of "reversibility" is important, i.e. if we add the decomposition, we get the original quotient. Always. At all points. I.e. we do not lose a pip of initial data.
The analytical component to the piggy bank. Let us begin to deal with the remainder. If the form of the analytical curve is successful, then the residue is well analyzed by the methods of statistics. Approximately like this.