Two independent random vectors are almost surely non-orthogonal

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SUMMARY

The discussion centers on the independence and orthogonality of three random vectors, X, Y, and Z, drawn from a continuous random distribution. It is established that Z, being independent of X and Y, will almost surely not be orthogonal to X (ZTX ≠ 0). Conversely, Y, defined as a non-linear function of X (Y = f(X)), does not guarantee that X will be orthogonal to Y (YTX = 0) almost surely. The probability of any two vectors being orthogonal in a continuous distribution is zero, confirming that the vectors are almost surely non-orthogonal.

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husseinshatri
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Hi all,

I got stuck with the following problem:

Let X, Y and Z be three random vectors of the same length drawn from a continuous random distribution.

where
Z is independent of X and Y but Y=f(X) with a non-linear function f.

Can I claim that:

1. Z^{T}X\neq 0 almost surely (i.e., vector X wouldn't almost surely lay on the null space of vector Z),

or

2. Y^{T}X= 0 almost surely (i.e., vector X would almost surely lay on the null space of vector Y).

If so, could you give me a hint to the proof or a citation.

Thank you for your help in advance.

Hussein
 
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husseinshatri said:
Hi all,

I got stuck with the following problem:

Let X, Y and Z be three random vectors of the same length drawn from a continuous random distribution.

where
Z is independent of X and Y but Y=f(X) with a non-linear function f.

Hussein

What do you mean by a random distribution? Are you randomly selecting from a set of distributions? Individual probability distributions are described by functions which are not themselves random. That is, their parameters are specified. Secondly, if three vectors are randomly selected from a population with a known or unknown probability distribution, how do two of these vectors (X and Y) come to be related by a non linear function? I assume you're talking about a population of three component vectors, all of the same length and sharing the same vector space.

I do agree that if you randomly select three vectors from a population where the orientations are randomly distributed on a continuous distribution, the probability that they would be orthogonal is zero. The probability of an exact value on a continuous distribution is zero by the definition of a continuum, in this case: all real numbers on the interval [0,1]. The same would be true for any pair from {X,Y,Z}.

EDIT: If you are talking about three random vectors in a 2-space, then only 2 vectors can be mutually orthogonal, the third being a linear combination of the other two. Was that part of your question?
 
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