Vector Space
Dependencies:
A vector space $V$ over a field $F$ is a set with a vector addition operation ($V \times V \mapsto V$) and a scalar multiplication operation ($F \times V \mapsto V$) that satisfies all of these axioms:
- $(V, +)$ is a commutative group.
- Scalar associativity: $\forall a \in F, \forall b \in F, \forall v \in V, a(bv) = (ab)v$.
- Distributivity: $\forall a \in F, \forall b \in F, \forall v \in V, (a+b)v = (av + bv)$.
- Distributivity: $\forall a \in F, \forall u \in V, \forall v \in V, a(u+v) = (au + av)$.
- Unit scalar: $\forall v \in V, 1v = v$.
The elements of $V$ are called vectors. The elements of $F$ are called scalars.
Two examples of vector spaces are $F$ and ${\mathbf{0}}$ (it is trivial to prove that they are vector spaces).
Dependency for:
- Convex function
- Linearity of expectation
- Expected value of a random variable
- Convex set
- Convex combination and convex hull
- Cone
- Linear transformation
- Inner product space
- Incrementing a linearly independent set
- Span
- Linearly independent set is not bigger than a span
- Negation in vector space
- Condition for being a subspace
- span(A)=span(B) & |A|=|B| & A is linindep ⟹ B is linindep
- Zeros in vector space
- Affine independence (incomplete)
- Linear independence
- Dimension of a set of vectors
- Decrementing a span
- Basis of a vector space
- Basis of F^n
- Matrices over a field form a vector space
- Row space
- Vector matroid
Info:
- Depth: 3
- Number of transitive dependencies: 3