Realvalued function
In mathematics, a realvalued function is a function whose values are real numbers. In other words, it is a function that assigns a real number to each member of its domain.
Function  

x ↦ f (x)  
Examples by domain and codomain  


Classes/properties  
Constant · Identity · Linear · Polynomial · Rational · Algebraic · Analytic · Smooth · Continuous · Measurable · Injective · Surjective · Bijective  
Constructions  
Restriction · Composition · λ · Inverse  
Generalizations  
Partial · Multivalued · Implicit  
Realvalued functions of a real variable (commonly called real functions) and realvalued functions of several real variables are the main object of study of calculus and, more generally, real analysis. In particular, many function spaces consist of realvalued functions.
Algebraic structure
Let be the set of all functions from a set X to real numbers . Because is a field, may be turned into a vector space and a commutative algebra over the reals with the following operations:
 – vector addition
 – additive identity
 – scalar multiplication
 – pointwise multiplication
These operations extend to partial functions from X to with the restriction that the partial functions f + g and f g are defined only if the domains of f and g have a nonempty intersection; in this case, their domain is the intersection of the domains of f and g.
Also, since is an ordered set, there is a partial order
on which makes a partially ordered ring.
Measurable
The σalgebra of Borel sets is an important structure on real numbers. If X has its σalgebra and a function f is such that the preimage f ^{−1}(B) of any Borel set B belongs to that σalgebra, then f is said to be measurable. Measurable functions also form a vector space and an algebra as explained above.
Moreover, a set (family) of realvalued functions on X can actually define a σalgebra on X generated by all preimages of all Borel sets (or of intervals only, it is not important). This is the way how σalgebras arise in (Kolmogorov's) probability theory, where realvalued functions on the sample space Ω are realvalued random variables.
Continuous
Real numbers form a topological space and a complete metric space. Continuous realvalued functions (which implies that X is a topological space) are important in theories of topological spaces and of metric spaces. The extreme value theorem states that for any real continuous function on a compact space its global maximum and minimum exist.
The concept of metric space itself is defined with a realvalued function of two variables, the metric, which is continuous. The space of continuous functions on a compact Hausdorff space has a particular importance. Convergent sequences also can be considered as realvalued continuous functions on a special topological space.
Continuous functions also form a vector space and an algebra as explained above, and are a subclass of measurable functions because any topological space has the σalgebra generated by open (or closed) sets.
Smooth
Real numbers are used as the codomain to define smooth functions. A domain of a real smooth function can be the real coordinate space (which yields a real multivariable function), a topological vector space,[1] an open subset of them, or a smooth manifold.
Spaces of smooth functions also are vector spaces and algebras as explained above, and are a subclass of continuous functions.
Appearances in measure theory
A measure on a set is a nonnegative realvalued functional on a σalgebra of subsets.[2] L^{p} spaces on sets with a measure are defined from aforementioned realvalued measurable functions, although they are actually quotient spaces. More precisely, whereas a function satisfying an appropriate summability condition defines an element of L^{p} space, in the opposite direction for any f ∈ L^{p}(X) and x ∈ X which is not an atom, the value f(x) is undefined. Though, realvalued L^{p} spaces still have some of the structure explicated above. Each of L^{p} spaces is a vector space and have a partial order, and there exists a pointwise multiplication of "functions" which changes p, namely
For example, pointwise product of two L^{2} functions belongs to L^{1}.
Other appearances
Other contexts where realvalued functions and their special properties are used include monotonic functions (on ordered sets), convex functions (on vector and affine spaces), harmonic and subharmonic functions (on Riemannian manifolds), analytic functions (usually of one or more real variables), algebraic functions (on real algebraic varieties), and polynomials (of one or more real variables).
See also
 Real analysis
 Partial differential equations, a major user of realvalued functions
 Norm (mathematics)
 Scalar (mathematics)
Footnotes
 Different definitions of derivative exist in general, but for finite dimensions they result in equivalent definitions of classes of smooth functions.
 Actually, a measure may have values in [0, +∞]: see extended real number line.