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When I tried to find this Rayleigh distribution Mathematica couldn't come with an answer:

PDF[TransformedDistribution[
  Sqrt[x1^2 + x2^2], {x1 \[Distributed] 
    NormalDistribution[μ1, σ], 
   x2 \[Distributed] NormalDistribution[μ2, σ]}, 
  Assumptions -> μ1 == μ2 == 0], r]

I want to derive the Rayleigh distribution in parametric form. Mathematica could solve this for N~[0,1] and the answer is Rayleigh[1], but for N~[0,k] it has no answer.

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  • 2
    $\begingroup$ Why not to use the RayleighDistribution? $\endgroup$
    – m0nhawk
    Commented Apr 11, 2015 at 15:37
  • 3
    $\begingroup$ Well, computer algebra systems can't solve every problem you throw at them. Questions like "why can't Mathematica solve it" are not a very good fit here usually. If the question is "how to compute this", then the anwser is what m0nhawk said. $\endgroup$
    – Szabolcs
    Commented Apr 11, 2015 at 15:38
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    $\begingroup$ @Szabolcs My shrink used to answer all my questions like that. $\endgroup$
    – Dr. belisarius
    Commented Apr 11, 2015 at 15:42
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    $\begingroup$ @OP What is your question? $\endgroup$
    – shrx
    Commented Apr 11, 2015 at 18:11
  • $\begingroup$ My Question is how Can I Solve this using Mathematica Mathematica Solve this Problem for Normal Distribution ~ [0,1] and returns RayleighDistribution[1] but for Normal Distribution~[0,k] has no Answer!!! $\endgroup$
    – Hamid reza
    Commented Apr 12, 2015 at 6:05

2 Answers 2

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You can use BinormalDistribution instead of two univariate normal distributions:

TransformedDistribution[Sqrt[x1^2 + x2^2],
 {x1, x2} ~Distributed~ BinormalDistribution[{0, 0}, {σ, σ}, 0]]
(* RayleighDistribution[σ] *)

TransformedDistribution[Sqrt[x1^2 + x2^2],
  {x1, x2} ~Distributed~ BinormalDistribution[{m, m}, {σ, σ}, 0]]
(* RiceDistribution[Sqrt[2] m, σ] *)

TransformedDistribution[Sqrt[x1^2 + x2^2],
 {x1, x2 } ~Distributed~ BinormalDistribution[{m1, m2}, {σ1, σ2}, 0]]
(* BeckmannDistribution[m1, m2, σ1, σ2, 0] *)
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  • $\begingroup$ Thanks a lot @Simon! This Solution is very better!!! $\endgroup$
    – Hamid reza
    Commented Apr 12, 2015 at 12:50
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You can get the desired result in two steps:

d1 = TransformedDistribution[x1^2 + x2^2, 
      {Distributed[x1, NormalDistribution[0, σ]], 
       Distributed[x2, NormalDistribution[0, σ]]}]
(* ExponentialDistribution[1/(2 σ^2)] *)

d2 = TransformedDistribution[Sqrt[z], Distributed[z, d1]]
(* RayleighDistribution[σ] *)

PDF[d2,r]

$\begin{cases} \frac{r e^{-\frac{r^2}{2 \sigma ^2}}}{\sigma ^2} & r>0 \\ 0 & \text{True} \end{cases}$

You can also fold the two steps into a single step:

With[{d1 =TransformedDistribution[x1^2 + x2^2, 
     {Distributed[x1, NormalDistribution[0, σ]], 
      Distributed[x2, NormalDistribution[0, σ]]}]}, 
TransformedDistribution[Sqrt[z], Distributed[z, d1]]]
(*  RayleighDistribution[σ] *)

Update: The results above are obtained in Version 9.0.1.0. As noted by @m0nhawk in the comments, in version 10, TransformedDistribution[Sqrt[z], Distributed[z, d1]] gives the result

WeibullDistribution[2, Sqrt[2] σ]

which is equivalent to RayleighDistribution[σ]:

PDF[WeibullDistribution[2, Sqrt[2] σ], r] == PDF[d2, r]
(* True *)
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  • $\begingroup$ I'm getting WeibullDistribution[2, Sqrt[2]/Sqrt[1/\[Sigma]^2]] for d2. Mathematica 10.1. $\endgroup$
    – m0nhawk
    Commented Apr 12, 2015 at 9:51
  • $\begingroup$ @m0nhawk, interesting. I am using v9.0.1.0. Btw, WeibullDistribution[2, Sqrt[2] σ] is equivalent to RayleighDistribution[σ]. $\endgroup$
    – kglr
    Commented Apr 12, 2015 at 9:57
  • $\begingroup$ Yeah, I know, I just provide a usefull information that other Mathematica version have other output. $\endgroup$
    – m0nhawk
    Commented Apr 12, 2015 at 9:58
  • $\begingroup$ @m0nhawk, thank you. Updated with a note on the version 10 output. $\endgroup$
    – kglr
    Commented Apr 12, 2015 at 10:04
  • $\begingroup$ Mathematica Should do this Automatically but didn't! is This a Bug? $\endgroup$
    – Hamid reza
    Commented Apr 12, 2015 at 10:33

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