Affine combination

In mathematics, an affine combination of x₁, ..., x_n is a linear combination

$\sum _{i=1}^{n}{\alpha _{i}\cdot x_{i}}=\alpha _{1}x_{1}+\alpha _{2}x_{2}+\cdots +\alpha _{n}x_{n},$

such that

$\sum _{i=1}^{n}{\alpha _{i}}=1.$

Here, x₁, ..., x_n can be elements (vectors) of a vector space over a field K, and the coefficients $\alpha _{i}$ are elements of K.

The elements x₁, ..., x_n can also be points of a Euclidean space, and, more generally, of an affine space over a field K. In this case the $\alpha _{i}$ are elements of K (or $\mathbb {R}$ for a Euclidean space), and the affine combination is also a point. See Affine space § Affine combinations and barycenter for the definition in this case.

This concept is fundamental in Euclidean geometry and affine geometry, as the set of all affine combinations of a set of points form the smallest subspace containing the points, exactly as the linear combinations of a set of vectors form their linear span.

The affine combinations commute with any affine transformation T in the sense that

$T\sum _{i=1}^{n}{\alpha _{i}\cdot x_{i}}=\sum _{i=1}^{n}{\alpha _{i}\cdot Tx_{i}}.$

In particular, any affine combination of the fixed points of a given affine transformation $T$ is also a fixed point of $T$, so the set of fixed points of $T$ forms an affine subspace (in 3D: a line or a plane, and the trivial cases, a point or the whole space).

When a stochastic matrix, A, acts on a column vector, b→, the result is a column vector whose entries are affine combinations of b→ with coefficients from the rows in A.

See also

Related combinations

Further information: Linear combination § Affine, conical, and convex combinations

• Convex combination
• Conical combination
• Linear combination

Affine geometry

• Affine space
• Affine geometry
• Affine hull

References

• Gallier, Jean (2001), Geometric Methods and Applications, Berlin, New York: Springer-Verlag, ISBN 978-0-387-95044-0. See chapter 2.

External links

• Notes on affine combinations.