Raised cosine distribution

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Raised cosine
Probability density function

Cumulative distribution function

Parameters \mu \,(real)

s>0\,(real)

Support x\in [\mu -s,\mu +s]\,
pdf {\frac {1}{2s}}\left[1+\cos \left({\frac {x\!-\!\mu }{s}}\,\pi \right)\right]\,
CDF {\frac {1}{2}}\left[1\!+\!{\frac {x\!-\!\mu }{s}}\!+\!{\frac {1}{\pi }}\sin \left({\frac {x\!-\!\mu }{s}}\,\pi \right)\right]
Mean \mu \,
Median \mu \,
Mode \mu \,
Variance s^{2}\left({\frac {1}{3}}-{\frac {2}{\pi ^{2}}}\right)\,
Skewness 0\,
Ex. kurtosis {\frac {6(90-\pi ^{4})}{5(\pi ^{2}-6)^{2}}}\,
MGF {\frac {\pi ^{2}\sinh(st)}{st(\pi ^{2}+s^{2}t^{2})}}\,e^{{\mu t}}
CF {\frac {\pi ^{2}\sin(st)}{st(\pi ^{2}-s^{2}t^{2})}}\,e^{{i\mu t}}

In probability theory and statistics, the raised cosine distribution is a continuous probability distribution supported on the interval [\mu -s,\mu +s]. The probability density function is

f(x;\mu ,s)={\frac {1}{2s}}\left[1+\cos \left({\frac {x\!-\!\mu }{s}}\,\pi \right)\right]\,

for \mu -s\leq x\leq \mu +s and zero otherwise. The cumulative distribution function is

F(x;\mu ,s)={\frac {1}{2}}\left[1\!+\!{\frac {x\!-\!\mu }{s}}\!+\!{\frac {1}{\pi }}\sin \left({\frac {x\!-\!\mu }{s}}\,\pi \right)\right]

for \mu -s\leq x\leq \mu +s and zero for x<\mu -s and unity for x>\mu +s.

The moments of the raised cosine distribution are somewhat complicated, but are considerably simplified for the standard raised cosine distribution. The standard raised cosine distribution is just the raised cosine distribution with \mu =0 and s=1. Because the standard raised cosine distribution is an even function, the odd moments are zero. The even moments are given by:

E(x^{{2n}})={\frac {1}{2}}\int _{{-1}}^{1}[1+\cos(x\pi )]x^{{2n}}\,dx
={\frac {1}{n\!+\!1}}+{\frac {1}{1\!+\!2n}}\,_{1}F_{2}\left(n\!+\!{\frac {1}{2}};{\frac {1}{2}},n\!+\!{\frac {3}{2}};{\frac {-\pi ^{2}}{4}}\right)

where \,_{1}F_{2} is a generalized hypergeometric function.

See also

References

 
Continuous univariate supported on a bounded interval, e.g. [0,1]
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