Share on Facebook Share on Twitter Email
Answers.com

Wigner semicircle distribution

 
Wikipedia: Wigner semicircle distribution
Wigner semicircle
Probability density function
Plot of the Wigner semicircle PDF
Cumulative distribution function
Plot of the Wigner semicircle CDF
Parameters R>0\! radius (real)
Support x \in [-R;+R]\!
Probability density function (pdf) \frac2{\pi R^2}\,\sqrt{R^2-x^2}\!
Cumulative distribution function (cdf) \frac12+\frac{x\sqrt{R^2-x^2}}{\pi R^2} + \frac{\arcsin\!\left(\frac{x}{R}\right)}{\pi}\!
for -R\leq x \leq R
Mean 0\,
Median 0\,
Mode 0\,
Variance \frac{R^2}{4}\!
Skewness 0\,
Excess kurtosis -1\,
Entropy \ln (\pi R) - \frac12 \,
Moment-generating function (mgf) 2\,\frac{I_1(R\,t)}{R\,t}
Characteristic function 2\,\frac{J_1(R\,t)}{R\,t}

The Wigner semicircle distribution, named after the physicist Eugene Wigner, is the probability distribution supported on the interval [−R, R] the graph of whose probability density function f is a semicircle of radius R centered at (0, 0) and then suitably normalized (so that it is really a semi-ellipse):

f(x)={2 \over \pi R^2}\sqrt{R^2-x^2\,}\,

for −R < x < R, and f(x) = 0 if x > R or x < − R.

This distribution arises as the limiting distribution of eigenvalues of many random symmetric matrices as the size of the matrix approaches infinity.

It is a scaled beta distribution, more precisely, if Y is beta distributed with parameters α = β = 3/2, then X = 2RYR has the above Wigner semicircle distribution.

Contents

General properties

The Chebyshev polynomials of the second kind are orthogonal polynomials with respect to the Wigner semicircle distribution.

For positive integers n, the 2n-th moment of this distribution is

E(X^{2n})=\left({R \over 2}\right)^{2n} C_n\,

where X is any random variable with this distribution and Cn is the nth Catalan number

C_n={1 \over n+1}{2n \choose n},\,

so that the moments are the Catalan numbers if R = 2. (Because of symmetry, all of the odd-order moments are zero.)

Making the substitution x = Rcos(θ) into the defining equation for the moment generating function it can be seen that:

M(t)=\frac{2}{\pi}\int_0^\pi e^{Rt\cos(\theta)}\sin^2(\theta)\,d\theta

which can be solved (see Abramowitz and Stegun §9.6.18) to yield:

M(t)=2\,\frac{I_1(Rt)}{Rt}

where I1(z) is the modified Bessel function. Similarly, the characteristic function is given by:

\varphi(t)=2\,\frac{J_1(Rt)}{Rt}

where J1(z) is the Bessel function. (See Abramowitz and Stegun §9.1.20), noting that the corresponding integral involving sin(Rtcos(θ)) is zero.)

In the limit of R approaching zero, the Wigner semicircle distribution becomes a Dirac delta function.

Relation to free probability

In free probability theory, the role of Wigner's semicircle distribution is analogous to that of the normal distribution in classical probability theory. Namely, in free probability theory, the role of cumulants is occupied by "free cumulants", whose relation to ordinary cumulants is simply that the role of the set of all partitions of a finite set in the theory of ordinary cumulants is replaced by the set of all noncrossing partitions of a finite set. Just the cumulants of degree more than 2 of a probability distribution are all zero if and only if the distribution is normal, so also, the free cumulants of degree more than 2 of a probability distribution are all zero if and only if the distribution is Wigner's semicircle distribution.

See also

  • The W.s.d. is the limit of the Kesten-McKay distributions, as the parameter d tends to infinity.

References

External links


Search unanswered questions...
Enter a question here...
Search: All sources Community Q&A Reference topics
Best of the Web: Wigner semicircle distribution
Top

Some good "Wigner semicircle distribution" pages on the web:


Math
mathworld.wolfram.com
 
 
 

 

Copyrights:

Wikipedia. This article is licensed under the Creative Commons Attribution/Share-Alike License. It uses material from the Wikipedia article "Wigner semicircle distribution" Read more