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In [[mathematical analysis]] (in particular [[convex analysis]]) and [[optimization (mathematics)|optimization]], a '''proper convex function''' is a [[convex function]] ''f'' taking values in the [[extended real number line]] such that
 
:<math>f(x) < +\infty</math>
 
for at least one ''x'' and
 
:<math>f(x) > -\infty</math>
 
for every ''x''. That is, a convex function is ''proper'' if its [[effective domain]] is nonempty and it never attains <math>-\infty</math>.<ref name="AB">{{cite book|last1=Aliprantis|first1=C.D.|last2=Border|first2=K.C.|title=Infinite Dimensional Analysis: A Hitchhiker's Guide|edition=3|publisher=Springer|year=2007|isbn=978-3-540-32696-0|doi=10.1007/3-540-29587-9|page=254}}</ref> Convex functions that are not proper are called ''improper convex functions''.<ref>{{cite book|author=[[Rockafellar, R. Tyrrell]]|title=Convex Analysis|publisher=Princeton University Press|location=Princeton, NJ|year=1997|origyear=1970|isbn=978-0-691-01586-6|page=24}}</ref>
 
A ''proper concave function'' is any function ''g'' such that <math>f = -g</math> is a proper convex function.
 
== Properties ==
 
For every proper convex function ''f'' on '''R'''<sup>n</sup> there exist some ''b'' in '''R'''<sup>n</sup> and β in '''R''' such that
 
:<math>f(x) \ge x \cdot b - \beta</math>
 
for every ''x''.
 
The sum of two proper convex functions is not necessarily proper or convex. For instance if the sets <math>A \subset X</math> and <math>B \subset X</math> are [[convex set]]s in the [[vector space]] ''X'', then the [[Characteristic function (convex analysis)|indicator function]]s <math>I_A</math> and <math>I_B</math> are proper convex functions, but <math>I_A + I_B</math> is not convex (unless <math>A \cup B</math> is convex), and is identically equal to <math>+\infty</math> if <math>A \cap B = \emptyset</math>.
 
The [[infimal convolute|infimal convolution]] of two proper convex functions is convex but not necessarily proper convex.{{Citation needed|date=October 2011}}
 
== References ==
{{Reflist}}
 
[[Category:Convex analysis]]
[[Category:Types of functions]]

Revision as of 22:59, 14 January 2014

In mathematical analysis (in particular convex analysis) and optimization, a proper convex function is a convex function f taking values in the extended real number line such that

f(x)<+∞

for at least one x and

f(x)>−∞

for every x. That is, a convex function is proper if its effective domain is nonempty and it never attains −∞.[1] Convex functions that are not proper are called improper convex functions.[2]

A proper concave function is any function g such that f=−g is a proper convex function.

Properties

For every proper convex function f on Rn there exist some b in Rn and β in R such that

f(x)≥x⋅b−β

for every x.

The sum of two proper convex functions is not necessarily proper or convex. For instance if the sets A⊂X and B⊂X are convex sets in the vector space X, then the indicator functions IA and IB are proper convex functions, but IA+IB is not convex (unless A∪B is convex), and is identically equal to +∞ if A∩B=∅.

The infimal convolution of two proper convex functions is convex but not necessarily proper convex.Potter or Ceramic Artist Truman Bedell from Rexton, has interests which include ceramics, best property developers in singapore developers in singapore and scrabble. Was especially enthused after visiting Alejandro de Humboldt National Park.

References

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