Harman Patil (Editor)

Slash distribution

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Parameters
  
none

Median
  
0

Mean
  
Does not exist

Slash distribution

Support
  
x ∈ ( − ∞ , ∞ ) {\displaystyle x\in (-\infty ,\infty )}

PDF
  
φ ( 0 ) − φ ( x ) x 2 {\displaystyle {\frac {\varphi (0)-\varphi (x)}{x^{2}}}}

CDF
  
{ Φ ( x ) − [ φ ( 0 ) − φ ( x ) ] / x x ≠ 0 1 / 2 x = 0 {\displaystyle {\begin{cases}\Phi (x)-\left[\varphi (0)-\varphi (x)\right]/x&x\neq 0\\1/2&x=0\\\end{cases}}}

In probability theory, the slash distribution is the probability distribution of a standard normal variate divided by an independent standard uniform variate. In other words, if the random variable Z has a normal distribution with zero mean and unit variance, the random variable U has a uniform distribution on [0,1] and Z and U are statistically independent, then the random variable XZ / U has a slash distribution. The slash distribution is an example of a ratio distribution. The distribution was named by William H. Rogers and John Tukey in a paper published in 1972.

The probability density function (pdf) is

f ( x ) = φ ( 0 ) φ ( x ) x 2 .

where φ(x) is the probability density function of the standard normal distribution. The result is undefined at x = 0, but the discontinuity is removable:

lim x 0 f ( x ) = φ ( 0 ) 2 = 1 2 2 π

The most common use of the slash distribution is in simulation studies. It is a useful distribution in this context because it has heavier tails than a normal distribution, but it is not as pathological as the Cauchy distribution.

Differential equation

The pdf of the slash distribution is a solution of the following differential equation:

{ 2 π x f ( x ) + 2 π ( x 2 + 2 ) f ( x ) 2 = 0 , f ( 1 ) = 1 2 π 1 2 e π }

References

Slash distribution Wikipedia