Integral for (kind of) standard Cauchy distibution and an alternative solution.

In summary, the conversation discusses solving a mathematical problem involving limits and integrals. One person shares their reasoning and solution, while another person suggests another method to confirm the correct answer. The conversation ends with the person stating their confidence in the accuracy of their results.
  • #1
nobahar
497
2
Hello!

I have a couple of questions on the following. Firstly, I was hoping someone could check my working and my reasoning.
Secondly, I was wondering if someone knew an alternative way of solving this problem.

I wanted to integrate this from [itex]x = -\infty[/itex] to [itex]x = \infty[/itex]:
[tex]\lim_{a \rightarrow 0^{\pm}} \left(\frac{a}{\pi(x^2 + a^2)}\right)[/tex]
It looks kind of like the standard Cauchy distribution-thingy...

I figured since [itex]a \neq 0[/itex] then I can ignore the limit (##a## could just be a really small number, for example, or a large number, and, as a constant, except for the sign it wouldn't make a difference what its value is). I put [itex]a \rightarrow 0^{\pm}[/itex] rather than just ##a \rightarrow 0## because the limit is different from either side, which is also important. I think...

Therefore:

[tex]\int_{-\infty}^{\infty} \left( \lim_{a \rightarrow 0^{\pm}} \left(\frac{a}{\pi(x^2 + a^2)}\right) \right) dx = \lim_{a \rightarrow 0^{\pm}} \left( \int_{-\infty}^{\infty}\frac{a}{\pi(x^2 + a^2)} dx \right)[/tex]

I used a trig substitution [itex]x = a \ tan(\theta)[/itex] since the range of ##\theta## is the same as x: [itex]-\infty < \tan(\theta) < \infty[/itex]. To change the endpoints to ##\theta##, for a>0 I get the lower bound to be [itex]\frac{-\pi}{2}[/itex] and the upper bound to be [itex]\frac{\pi}{2}[/itex], but for ##a<0## I get ##\frac{\pi}{2}## and ##\frac{-\pi}{2}## (they 'flip'); for the example, using ##a>0##:

[tex]\int_{-\infty}^{\infty}\frac{a}{(x^2 + a^2)} dx = \int_{\frac{-\pi}{2}}^{\frac{\pi}{2}}\frac{a}{\pi((a \tan(\theta))^2 + a^2)}\,a (\tan^2(\theta) + 1) d\theta = \int_{\frac{-\pi}{2}}^{\frac{\pi}{2}}\frac{a^2 (\tan^2(\theta) + 1)}{\pi a^2 (\tan^2(\theta) + 1)} d\theta[/tex]

[tex]= \frac{a^2}{\pi a^2} \int_{\frac{-\pi}{2}}^{\frac{\pi}{2}} d\theta = \frac{a^2}{\pi a^2} \left( \theta \Biggr|_{\frac{-\pi}{2}}^{\frac{\pi}{2}} \right) = \frac{a^2}{\pi a^2} \left(\frac{\pi}{2} + \frac{\pi}{2}\right) = 1[/tex]

Evaluating the integral without converting back to x, for ##a>0## I get +1, as above. For ##a<0##, I get -1 (because the endpoints would be the other way up).
The ##a## constants cancelled, but ##a## impacted on the sign of the final value. I'm guessing this is necessary to consider when stating the limit: either a right-hand limit or a left-hand limit.

I want to convert back to x so that someone could check my reasoning if that's okay.

I get [itex]\theta = \arctan{\frac{x}{a}}[/itex].
Here then, I would have to apply the endpoints for x, that is ##\infty## and ##-\infty##. To do this, I believe limits are applied to constants for the endpoints: the upper bound is ##\beta##, the lower bound is ##\alpha##, and:

[tex]\frac{a^2}{\pi a^2} \left(\lim_{\beta \rightarrow \infty} \left(\arctan{\frac{\beta}{a}}\right) - \lim_{\alpha \rightarrow -\infty} \left(\arctan{\frac{\alpha}{a}}\right)\right)[/tex]

Again, this gives +1 if ##a>0##, and -1 if ##a<0##, since arctan(x/a) changes sign if ##a## changes sign.

I'm guessing it is at this point that I can re-introduce the limit for ##a \rightarrow 0^{\pm}##. As ##a \rightarrow 0^{\pm}##, ##\frac{1}{a} \rightarrow \pm\infty##; For ##\frac{x}{a}##, both ##x## and ##a## want to take the value to either positive or negative infinity. For ##a \rightarrow 0^{+}##, ##\frac{\beta}{a} \rightarrow \infty## and ##\frac{\alpha}{a} \rightarrow -\infty##; and for ##a \rightarrow 0^{-}##, ##\frac{\beta}{a} \rightarrow -\infty## and ##\frac{\alpha}{a} \rightarrow \infty##. Therefore:

[tex]\lim_{a \rightarrow 0^{+}} \left( \frac{a^2}{\pi a^2} \left(\lim_{\beta \rightarrow \infty} \left(\arctan{\frac{\beta}{a}}\right) - \lim_{\alpha \rightarrow -\infty} \left(\arctan{\frac{\alpha}{a}}\right)\right) \right) = \frac{a^2}{\pi a^2} \left(\frac{\pi}{2} - \frac{-\pi}{2}\right) = \frac{a^2}{\pi a^2} \left(\frac{\pi}{2} + \frac{\pi}{2}\right) = 1[/tex]

or

[tex]\lim_{a \rightarrow 0^{-}} \left( \frac{a^2}{\pi a^2} \left(\lim_{\beta \rightarrow \infty} \left(\arctan{\frac{\beta}{a}}\right) - \lim_{\alpha \rightarrow -\infty} \left(\arctan{\frac{\alpha}{a}}\right)\right) \right) = \frac{a^2}{\pi a^2} \left(\frac{-\pi}{2} - \frac{\pi}{2}\right) = -1[/tex]

Okay, in both cases - either substituting back or not - I get the same results. However, as mentioned earlier, the limit is different from both sides for the limit of ##a##; this means I would have to explicitly state the direction for it to be meaningful, but the limit still exists. Is this in any way accurate?

The other question concerns an alternative solution to the integral. Wolfram Alpha churns out:
[tex]a \sqrt{\frac{1}{a^2}}[/tex]
It's also possible to see from this how the direction of the limit for ##a## affects the value, being 1 or -1. Does anyone know how wolfram got this solution?

Any help appreciated.
 
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  • #2
Your result seems correct to me.
I'm guessing Wolfram has tables with definite integrals such as int 1/(x^2+1)=pi
Since you want further proof that your answer is correct, here are two things you can do:
- substitute y=x/|a| first. the modulus of a makes sure that you don't have to swap your upper and lower bound in the integral. this reduces your expression to the standard cauchy distribution one times a*|a|/a^2=sgn(a).
- if you want an entirely alternative proof, you can try contour integration.
http://en.wikipedia.org/wiki/Method...xample_.28II.29_.E2.80.93_Cauchy_distribution
You can see that depending on the nominator's sign, you only enclose one of the two singularities.
 
  • #3
susskind_leon said:
Your result seems correct to me.
I'm guessing Wolfram has tables with definite integrals such as int 1/(x^2+1)=pi
Since you want further proof that your answer is correct, here are two things you can do:
- substitute y=x/|a| first. the modulus of a makes sure that you don't have to swap your upper and lower bound in the integral. this reduces your expression to the standard cauchy distribution one times a*|a|/a^2=sgn(a).

Hi susskind, thanks for the response.
Phew, all those limits and infinities hurt my brain, good to see it worked out in the end!
Ihave never seen the signum function before - it doesn't look that familiar, anyway. When you use the y = x/|a| substitution, is the following correct?:

[tex]\frac{a}{\pi(x^{2}+a^{2})} = \frac{sgn(a)|a|}{\pi|a|^{2}}\frac{1}{(y^{2}+1)}[/tex]

and therefore, using |a|dy = dx:

[tex]\frac{sgn(a)|a|^{2}}{\pi|a|^{2}}\int_{-\infty}^{\infty}\frac{1}{(y^{2}+1)}dy = sgn(a)[/tex]

susskind_leon said:
...if you want an entirely alternative proof, you can try contour integration.
http://en.wikipedia.org/wiki/Method...xample_.28II.29_.E2.80.93_Cauchy_distribution
You can see that depending on the nominator's sign, you only enclose one of the two singularities.

I don't know what this means! Your assertion that my results are accurate and your method of using sgn(a) is sufficient for me at this point.
Many thanks for all the help!
 
  • #4
You got it, dude, because [itex]a=sgn(a)*|a|[/itex]
This is probably the quickest way if you already know that [itex]\int_{-\infty}^\infty \frac{1}{1+x^2}dx=\pi[/itex]
 
  • #5
Thaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaankyoooooooouuuuuuuuuuuuuuuuuu!
 
  • #6
You're weeeeeeeeeeeeeeeeeelcooooooooooooooooooooooome ;-)
 

1. What is the standard Cauchy distribution?

The standard Cauchy distribution is a probability distribution that is symmetric about its mean, which is also its median and mode. It has long tails and a single peak at its center, making it a heavy-tailed distribution. It is often used to model rare events or extreme values in statistical analyses.

2. What is the integral for the standard Cauchy distribution?

The integral for the standard Cauchy distribution is not defined in the traditional sense, as it does not have a finite area under the curve. This is due to the long tails of the distribution, which never approach zero. However, it can still be approximated using numerical integration methods.

3. What is an alternative solution to finding the integral for the standard Cauchy distribution?

An alternative solution is to use the Cauchy principal value, which is the average of the left and right limits of the integral. This approach can be useful when dealing with integrals that do not have a well-defined value, such as the standard Cauchy distribution.

4. How is the standard Cauchy distribution related to the normal distribution?

The standard Cauchy distribution is closely related to the normal distribution, as it can be derived by dividing two independent standard normal random variables. However, unlike the normal distribution, the Cauchy distribution does not have a finite mean or variance, making it more suitable for modeling extreme values.

5. What are some real-world applications of the standard Cauchy distribution?

The standard Cauchy distribution is commonly used in fields such as engineering, economics, and social sciences to model rare events or extreme values. It is also used in Bayesian statistics and in the calculation of confidence intervals. Examples of real-world applications include modeling stock market returns, analyzing environmental disasters, and predicting extreme weather events.

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