Given a subset of a larger set, the characteristic function
, sometimes also called the indicator function, is the
function defined to be identically one on
, and is zero elsewhere. Characteristic functions are sometimes
denoted using the so-called Iverson bracket, and
can be useful descriptive devices since it is easier to say, for example, "the
characteristic function of the primes" rather than repeating a given definition.
A characteristic function is a special case of a simple
function.
The term characteristic function is used in a different way in probability, where it is denoted
and is defined as the Fourier transform of the
probability density function using
Fourier transform parameters
,
(1)
| |||
(2)
| |||
(3)
| |||
(4)
| |||
(5)
|
where
(sometimes also denoted
) is the
th moment about 0 and
(Abramowitz and Stegun 1972, p. 928; Morrison
1995).
A statistical distribution is not uniquely specified by its moments, but is by its characteristic function if all of its moments are finite and the series for its characteristic function converges absolutely near the origin (Papoulis 1991, p. 116). In this case, the probability density function is given by
(6)
|
(Papoulis 1991, p. 116).
The characteristic function can therefore be used to generate raw moments,
(7)
|
or the cumulants ,
(8)
|