Discussing the article: "Hilbert-Schmidt Independence Criterion (HSIC)" - page 3
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There is a good old Spearman rank for nonlinearities. Still, the article is more serious.
There's a good old Spearman rank for non-linearity. Still, the article is more serious.
The loss of information is huge. Trend, seasonality and cycles are removed. That's two different time series.
I guess we're not talking about the same thing.
I guess we're not talking about the same thing.
Alexei Nikolaev will explain it better, I rarely get it :) maybe I'm wrong in this case, but it seems the opposite to me.
You're restless,
like this Jamaican me, who has no time for anything.you've been resting,
like this Jamaican me who has no time for me.I'm like a dog. I understand everything, but I can't say anything.
If you misbehave, you won't get fresh sausage.
If you misbehave, you won't get fresh sausage.
Why hasn't anyone asked the most interesting question? How to use it?
Where do I put the iClose(character1) and iClose(character2) data to compare them?
I wanted to do a comparison with Pearson. There in the code Pearson counts on (X1, Y) and on (X2, Y) - independently.
And then, when calculating hsic_Gamma_test() X1 and X2 are shoved into one matrix.... and some 'mystical pairing' of matrix X (from two columns) with matrix Y from one column is performed
.
Can't hsic_Gamma_test() just be calculated like that - over two one-dimensional rows? Well, or
not hsic_Gamma_test(), but at least something that is the subject of this article.
Of course, I tried to make one column at X... something counted... some result
is there.... But what is it? If we knew what it is, and we don't know what it is.....