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Given the following p.d.f., which is the p.d.f. of the real and imaginary parts of a random variable that is the ratio between a complex Gaussian and a Chi-squared RVs:

\begin{equation*} f_U(u)=\exp\Big\{{-\frac{1}{4 u^2}}\Big\} \,\frac{\left(8 n u^2-1\right) I_n\left(\frac{1}{4 u^2}\right)+I_{n+1}\left(\frac{1}{4 u^2}\right)}{4 |u|^3}, \end{equation*} where $n$ is a constant integer and $I_n(z)$ is the modified Bessel function of the first kind.

I'd like to find its Cumulative distribution function (CDF).

Further information on this p.d.f. and how it was obtained can be found at: Distribution of ratio between complex Gaussian and Chi-square R.V.s

I've tried to solve with Mathematica:

ii = 1/Pi Integrate[w^(-1 - n) Exp[(-b*v)/(a*w)] 1/Sqrt[w - u^2], {w,u^2, \[Infinity]}, Assumptions -> (u > 0 && n > 2 && 1 > v > 0 && a > 0 && b > 0)]
jj = (b^n)/((n - 2)! a^n) Integrate[v^n (1 - v)^(n - 2) ii, {v, 0, 1}, Assumptions -> (u > 0 && n > 2 && a > 0 && b > 0)]
Integrate[jj, {u, -Infinity, t}, Assumptions -> (u > 0 && n > 2 && a > 0 && b > 0)]

but it gives out a solution with this Hypergeometric function. I wonder if there is a tricky or some other technique to find a simpler equation for the CDF.

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    $\begingroup$ I am surprised that you get something as simple as Mathematica's hypergeometric answer. I don't think that you can reasonably ask for anything better than that. $\endgroup$ Commented Feb 19, 2019 at 9:12
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    $\begingroup$ Not sure if helpful, but your Bessel functions should simplify, $(8 n u^2-1) \, I_n(\frac{1}{4 u^2}) + I_{n+1}(\frac{1}{4 u^2}) = I_{n-1}(\frac{1}{4 u^2}) - I_n(\frac{1}{4 u^2})$. Also, the form is very close to $(\partial_z + n/z) \, \exp\{-z\} \, I_n(z)$, so there might just be an expression? $\endgroup$
    – user114668
    Commented Feb 19, 2019 at 10:21
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    $\begingroup$ ... which of course means the whole thing is essentially $z^{-n} \partial_z \, z^n \exp\{-z\} \, I_n(z)$. $\endgroup$
    – user114668
    Commented Feb 19, 2019 at 10:31
  • $\begingroup$ @student, what does $\partial_{z}$ mean? $\endgroup$ Commented Feb 19, 2019 at 11:54
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    $\begingroup$ I was merely pointing out that it is not entirely unreasonable to expect a closed form since the function is close to a derivative itself. But I had not considered that the PDF is a second derivative of the CDF for a complex random variable. So I doubt you can do much better than the accepted answer, unless the polynomials turn out to be of something nice. $\endgroup$
    – user114668
    Commented Feb 19, 2019 at 21:50

1 Answer 1

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The cumulative distribution function you are seeking is $$F_n(x)=2\int_0^{x}\exp\left({-\frac{1}{4 u^2}}\right) \,\frac{\left(8 n u^2-1\right) I_n\left(\frac{1}{4 u^2}\right)+I_{n+1}\left(\frac{1}{4 u^2}\right)}{4 u^3}\, du.$$ It has the general form $$F_n(x)=e^{-1/z}\bigl(A_n(z)I_0(1/z)+B_n(z)I_1(1/z)\bigr),$$ with $A_n(z)$ a polynomial in $z=4x^2$ of degree $\max(0,n-3)$ and $B_n(z)$ a polynomial in $z$ of degree $\max(0,n-2)$. For $n\in\{1,2,\ldots 10\}$ I find $$\{A_n\}=\left\{1,1,3,3-8 z,48 z^2-8 z+5,-384 z^3+48 z^2-32 z+5,3840 z^4-384 z^3+336 z^2-32 z+7,-46080 z^5+3840 z^4-4224 z^3+336 z^2-80 z+7,645120 z^6-46080 z^5+61440 z^4-4224 z^3+1296 z^2-80 z+9,-10321920 z^7+645120 z^6-1013760 z^5+61440 z^4-23424 z^3+1296 z^2-160 z+9\right\},$$ $$\{B_n\}=\left\{0,2,2-4 z,16 z^2-4 z+4,-96 z^3+16 z^2-20 z+4,768 z^4-96 z^3+160 z^2-20 z+6,-7680 z^5+768 z^4-1632 z^3+160 z^2-56 z+6,92160 z^6-7680 z^5+19968 z^4-1632 z^3+736 z^2-56 z+8,-1290240 z^7+92160 z^6-284160 z^5+19968 z^4-11232 z^3+736 z^2-120 z+8,20643840 z^8-1290240 z^7+4608000 z^6-284160 z^5+192768 z^4-11232 z^3+2336 z^2-120 z+10\right\}.$$ (I checked that $\lim_{x\rightarrow\infty}F_n(x)=1$, as it should be.)

Perhaps these are known sequences of polynomials, I don't know.

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  • $\begingroup$ Dear Carlo, do you know what $\partial_x$ means? Thanks. $\endgroup$ Commented Feb 19, 2019 at 18:43
  • $\begingroup$ certainly, $\partial_x$ is an abbreviation for $\partial/\partial x$ (so partial derivative with respect to $x$) $\endgroup$ Commented Feb 19, 2019 at 20:41

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