A question for the statisticians amongs us

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Discussion Overview

The discussion centers around the mathematical expression involving the limit of a sum of independent standard normal random variables, specifically questioning the definition and convergence of the expression \(0 \cdot \left(lim_{n \rightarrow \infty} \sum_{j=0}^n Z_j \right)\) and related limits involving different functions \(f(n)\).

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • Some participants argue that the expression \(0 \cdot \left(lim_{n \rightarrow \infty} \sum_{j=0}^n Z_j \right)\) is not well-defined due to the divergence of the sum.
  • Others suggest that while the expression itself is not well-defined, the limit \(lim_{n\to\infty}0\cdot \sum_{j=0}^n Z_j\) equals zero.
  • It is proposed that the limit \(lim_{n \rightarrow \infty}\frac{1}{\sqrt{n}}\sum_{j=0}^n Z_j\) is well-defined and diverges, with the mean of the Z's being a factor in this divergence.
  • Some participants clarify that if \(f(n) = n\), the limit results in zero, while if \(f(n) = \sqrt{n}\), the limit approaches a Gaussian random variable \(W \sim N(0,1)\).
  • There is a discussion about the implications of the law of large numbers on these limits, particularly regarding the behavior of the sums as \(n\) approaches infinity.

Areas of Agreement / Disagreement

Participants express differing views on the definition and convergence of the limits discussed. There is no consensus on the overall behavior of the expressions, as some argue for divergence while others provide conditions under which certain limits are well-defined.

Contextual Notes

Limitations include the dependence on the definitions of convergence and the behavior of sums of random variables. The discussion also highlights the need for careful consideration of the conditions under which limits are taken.

Apteronotus
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Suppose Zj are N(0,1).

[tex] 0\cdot \left(lim_{n \rightarrow \infty} \sum_{j=0}^n Z_j \right)[/tex]

Is this zero? or even defined at all?
 
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In order to multiply two quantities, both must be individually well-defined. In your case, the quantity in the parenthesis is not well-defined, since the sum does not converge (unless you are working in some strange space where the sum actually converges...?)

Torquil
 
[tex]0\cdot \left(lim_{n \rightarrow \infty} \sum_{j=0}^n Z_j \right)[/tex]
is not well-defined, but of course
[tex]lim_{n\to\infty}0\cdot \sum_{j=0}^n Z_j=0[/tex]
 
And of course,
[tex]\lim_{n\to\infty}{\left(\frac 1{f(n)} \cdot \sum_{j=0}^n Z_j\right)}[/tex]
is well-defined for [itex]f(n) = \sqrt n[/itex] and for [itex]f(n) = n[/itex].
 
Last edited:
EnumaElish said:
... is well-defined for [itex]f(n) = \sqrt n[/itex] ...

But if [tex]f(n)=\sqrt{n}[/tex] then

[tex] lim_{n \rightarrow \infty}\frac{1}{\sqrt{n}}\sum_{j=0}^n Z_j<br /> =lim_{n \rightarrow \infty}\frac{\sqrt{n}}{n}\sum_{j=0}^n Z_j<br /> =\left(lim_{n \rightarrow \infty}\sqrt{n}\right) \cdot \left(lim_{n \rightarrow \infty}\frac{1}{n}\sum_{j=0}^n Z_j\right)<br /> =\left(lim_{n \rightarrow \infty}\sqrt{n}\right) \cdot \mu[/tex]

by law of large numbers, where [tex]\mu[/tex] is the mean of the Z's. And consequently the limit diverges!
 
Apteronotus said:
But if [tex]f(n)=\sqrt{n}[/tex] then

[tex] lim_{n \rightarrow \infty}\frac{1}{\sqrt{n}}\sum_{j=0}^n Z_j<br /> =lim_{n \rightarrow \infty}\frac{\sqrt{n}}{n}\sum_{j=0}^n Z_j<br /> =\left(lim_{n \rightarrow \infty}\sqrt{n}\right) \cdot \left(lim_{n \rightarrow \infty}\frac{1}{n}\sum_{j=0}^n Z_j\right)<br /> =\left(lim_{n \rightarrow \infty}\sqrt{n}\right) \cdot \mu[/tex]

by law of large numbers, where [tex]\mu[/tex] is the mean of the Z's. And consequently the limit diverges!

Yes, that is as expected. E.g. the mean for finite [tex]n[/tex] is [tex]\mu\sqrt{n}[/tex], so this cannot converge.

This is unrelated to the expression of the Wiener process as a limit of finite-time difference increments, since in that case [tex]\mu=0[/tex] and therefore you cannot split the limit expression in the same way since you would then get "[tex]\infty\times 0[/tex]".

Torquil
 
So
1. why/how is the expression [tex] \lim_{n\to\infty}{\left(\frac 1{f(n)} \cdot \sum_{j=0}^n Z_j\right)}[/tex]
well defined for [tex]f(n)=sqrt n[/tex] as EnumaElish stated above?
and
2. what is its value?
 
Apteronotus said:
So
1. why/how is the expression [tex] \lim_{n\to\infty}{\left(\frac 1{f(n)} \cdot \sum_{j=0}^n Z_j\right)}[/tex]
well defined for [tex]f(n)=sqrt n[/tex] as EnumaElish stated above?

and
2. what is its value?

Assume that Exp[Z] = 0 and Var[Z] = 1, for all the Z's.

If you use f(n) = n then you get zero in the limit. You can prove this using the law of large numbers, as you did for one of the parenthesis you had above (just put your \mu=0).

If f(n) = sqrt(n), the limit is not a single number, but a gaussian random variable W ~ N(0,1). Notice that for each finite n, the expectations and variance of the truncated sum W_n is:

Exp[W_n] = 0, Var[W_n] = 1

This is true for finite n, and independent of n, so it is also true in the limit.
 

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