In mathematics , two positive (or signed or complex ) measures
μ μ -->
{\displaystyle \mu }
and
ν ν -->
{\displaystyle \nu }
defined on a measurable space
(
Ω Ω -->
,
Σ Σ -->
)
{\displaystyle (\Omega ,\Sigma )}
are called singular if there exist two disjoint measurable sets
A
,
B
∈ ∈ -->
Σ Σ -->
{\displaystyle A,B\in \Sigma }
whose union is
Ω Ω -->
{\displaystyle \Omega }
such that
μ μ -->
{\displaystyle \mu }
is zero on all measurable subsets of
B
{\displaystyle B}
while
ν ν -->
{\displaystyle \nu }
is zero on all measurable subsets of
A
.
{\displaystyle A.}
This is denoted by
μ μ -->
⊥ ⊥ -->
ν ν -->
.
{\displaystyle \mu \perp \nu .}
A refined form of Lebesgue's decomposition theorem decomposes a singular measure into a singular continuous measure and a discrete measure . See below for examples.
Examples on R n
As a particular case, a measure defined on the Euclidean space
R
n
{\displaystyle \mathbb {R} ^{n}}
is called singular , if it is singular with respect to the Lebesgue measure on this space. For example, the Dirac delta function is a singular measure.
Example. A discrete measure .
The Heaviside step function on the real line ,
H
(
x
)
=
d
e
f
{
0
,
x
<
0
;
1
,
x
≥ ≥ -->
0
;
{\displaystyle H(x)\ {\stackrel {\mathrm {def} }{=}}{\begin{cases}0,&x<0;\\1,&x\geq 0;\end{cases}}}
has the Dirac delta distribution
δ δ -->
0
{\displaystyle \delta _{0}}
as its distributional derivative . This is a measure on the real line, a "point mass " at
0.
{\displaystyle 0.}
However, the Dirac measure
δ δ -->
0
{\displaystyle \delta _{0}}
is not absolutely continuous with respect to Lebesgue measure
λ λ -->
,
{\displaystyle \lambda ,}
nor is
λ λ -->
{\displaystyle \lambda }
absolutely continuous with respect to
δ δ -->
0
:
{\displaystyle \delta _{0}:}
λ λ -->
(
{
0
}
)
=
0
{\displaystyle \lambda (\{0\})=0}
but
δ δ -->
0
(
{
0
}
)
=
1
;
{\displaystyle \delta _{0}(\{0\})=1;}
if
U
{\displaystyle U}
is any non-empty open set not containing 0, then
λ λ -->
(
U
)
>
0
{\displaystyle \lambda (U)>0}
but
δ δ -->
0
(
U
)
=
0.
{\displaystyle \delta _{0}(U)=0.}
Example. A singular continuous measure.
The Cantor distribution has a cumulative distribution function that is continuous but not absolutely continuous , and indeed its absolutely continuous part is zero: it is singular continuous.
Example. A singular continuous measure on
R
2
.
{\displaystyle \mathbb {R} ^{2}.}
The upper and lower Fréchet–Hoeffding bounds are singular distributions in two dimensions.
See also
References
Eric W Weisstein, CRC Concise Encyclopedia of Mathematics , CRC Press, 2002. ISBN 1-58488-347-2 .
J Taylor, An Introduction to Measure and Probability , Springer, 1996. ISBN 0-387-94830-9 .
This article incorporates material from singular measure on PlanetMath , which is licensed under the Creative Commons Attribution/Share-Alike License .