Convex combination explained

In convex geometry and vector algebra, a convex combination is a linear combination of points (which can be vectors, scalars, or more generally points in an affine space) where all coefficients are non-negative and sum to 1. In other words, the operation is equivalent to a standard weighted average, but whose weights are expressed as a percent of the total weight, instead of as a fraction of the count of the weights as in a standard weighted average.

Formal definition

More formally, given a finite number of points

x _{1,} x _{2,} ... , x _{n} in a real vector space, a convex combination of these points is a point of the form\alpha _{1x} _{1+\alpha} _{2x} _{2+ … +\alpha} _{nx} _{n} where the real numbers \alpha _{i} satisfy \alpha _{i\ge} 0 and \alpha _{1+\alpha} _{2+ … +\alpha} _{n=1.}

As a particular example, every convex combination of two points lies on the line segment between the points.

A set is convex if it contains all convex combinations of its points.The convex hull of a given set of points is identical to the set of all their convex combinations.

There exist subsets of a vector space that are not closed under linear combinations but are closed under convex combinations. For example, the interval

[ 0 , 1 ] is convex but generates the real-number line under linear combinations. Another example is the convex set of probability distributions, as linear combinations preserve neither nonnegativity nor affinity (i.e., having total integral one).

Other objects

• A random variable

X is said to have an n -component finite mixture distribution if its probability density function is a convex combination of n so-called component densities.

Related constructions

• A conical combination is a linear combination with nonnegative coefficients. When a point

x is to be used as the reference origin for defining displacement vectors, then x is a convex combination of n points x _{1,} x _{2,} ... , x _{n} if and only if the zero displacement is a non-trivial conical combination of their n respective displacement vectors relative to x .

• Weighted means are functionally the same as convex combinations, but they use a different notation. The coefficients (weights) in a weighted mean are not required to sum to 1; instead the weighted linear combination is explicitly divided by the sum of the weights.
• Affine combinations are like convex combinations, but the coefficients are not required to be non-negative. Hence affine combinations are defined in vector spaces over any field.

See also

• Affine hull
• Carathéodory's theorem (convex hull)
• Simplex
• Barycentric coordinate system
• Convex space

External links

• Convex sum/combination with a trianglr - interactive illustration
• Convex sum/combination with a hexagon - interactive illustration
• Convex sum/combination with a tetraeder - interactive illustration