
In
mathematics, a sequence = of nonnegative real numbers is called a logarithmically concave sequence, or a log-concave sequence for short, if holds for .
''Remark:'' some authors (explicitly or not) add two further conditions in the definition of log-concave sequences:
* is non-negative
* has no internal zeros; in other words, the
support
Support may refer to:
Arts, entertainment, and media
* Supporting character
Business and finance
* Support (technical analysis)
* Child support
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Construction
* Support (structure), or lateral support, a ...
of is an interval of .
These conditions mirror the ones required for
log-concave functions.
Sequences that fulfill the three conditions are also called Pólya Frequency sequences of order 2 (PF
2 sequences). Refer to chapter 2 of
for a discussion on the two notions. For instance, the sequence satisfies the concavity inequalities but not the internal zeros condition.
Examples of log-concave sequences are given by the
binomial coefficient
In mathematics, the binomial coefficients are the positive integers that occur as coefficients in the binomial theorem. Commonly, a binomial coefficient is indexed by a pair of integers and is written \tbinom. It is the coefficient of the t ...
s along any row of
Pascal's triangle
In mathematics, Pascal's triangle is a triangular array of the binomial coefficients that arises in probability theory, combinatorics, and algebra. In much of the Western world, it is named after the French mathematician Blaise Pascal, althoug ...
and the
elementary symmetric means of a finite sequence of real numbers.
References
*
See also
*
Unimodality
In mathematics, unimodality means possessing a unique mode. More generally, unimodality means there is only a single highest value, somehow defined, of some mathematical object.
Unimodal probability distribution
In statistics, a unimodal ...
*
Logarithmically concave function In convex analysis, a non-negative function is logarithmically concave (or log-concave for short) if its domain is a convex set, and if it satisfies the inequality
:
f(\theta x + (1 - \theta) y) \geq f(x)^ f(y)^
for all and . If is strict ...
*
Logarithmically concave measure
Sequences and series
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