Calculate the probability of reversal - page 9
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Well, there is no task to estimate distribution parameters)
What other way is there to choose a particular Gaussian among others, besides specifying its parameters? Any choice of a particular parameter value (based on the sample) is called estimation.
1. they are NOT insignificant. One such "minor" case could result in the loss of everything earned by the "major" ones.
3. linear correlation. MNC all the same, linear I called approximation, not MNC.
1. So probabilistic methods are not suitable for this analysis.
3. If you approximate with a straight line, why talk about "Gaussian"?
What other ways are there to select a particular Gaussian among others, besides specifying its parameters? Any choice of a particular parameter value (based on a sample) is called an estimate.
Minimum sum of squares of variance, for example. The parameters of the resulting Gaussian may not even be calculated, they are not important for analysing the difference between the two curves.
1. So probabilistic methods are not suitable for this analysis.
3. If you approximate with a straight line, why talk about "Gaussian"?
1. Rather, parametric methods are not suitable.
3. A straight line is obtained on the P-P plot, that's where it is approximated.
Minimum sum of squares of deviations, for example. The parameters of the resulting Gaussian may not even be calculated, they are not important for analyzing the difference between the two curves.
The parameters there are quite calculated (from the conditions of minimum SC over them) and then used to find the minimum SC. The usual school problem on function extrema.
1. Rather, parametric methods are unsuitable.
3. The straight line is obtained on the P-P plot and approximated there.
Well, that's an exchange of views. I don't think I can help you with the question of linear approximation of some data by a normal distribution. For me, a linear approximation is an approximation by a straight line, i.e. a polynomial of degree 1.
Well, that's an exchange of views. I don't think I can help you any further on the question of linear approximation of some data by a normal distribution. For me, a linear approximation is an approximation by a straight line, i.e. a polynomial of degree 1.
It is:
https://en.wikipedia.org/wiki/P-P_plot
Take two different parabolas, for example. There is a linear relationship between them. Although both curves are non-linear.Who knows the maths, please help me solve this problem, I can't figure out how to do it.
It's simple, the probability of reversal is always 50%, but if the probability of reversal is different from 50%, then the probability density graph will be different.
As you all know ANY problem can be solved in SEVERAL DIFFERENT ways...
For example:
1. You can try to PREPARATE a FUTURE trend reversal...
2. You may document a trend reversal in a CURRENT situation in the market...
As you understand, variant №1 is VERY difficult to solve with a high degree of reliability...
Option #2 is much easier, as you don't have to be a psychic like Vanga, and the positive results will be much higher than in the first option...
All in all: The RIGHT way of setting the problem gives more than half of its solution!