Maximum and minimum

In mathematical analysis, the maximum and minimum of a function are, respectively, the greatest and least value taken by the function. Known generically as extrema, they may be defined either within a given range (the local or relative extrema) or on the entire domain (the global or absolute extrema) of a function. Pierre de Fermat was one of the first mathematicians to propose a general technique, adequality, for finding the maxima and minima of functions.

As defined in set theory, the maximum and minimum of a set are the greatest and least elements in the set, respectively. Unbounded infinite sets, such as the set of real numbers, have no minimum or maximum.

In statistics, the corresponding concept is the sample maximum and minimum.

Definition

A real-valued function f defined on a domain X has a global (or absolute) maximum point at x∗, if f(x∗) ≥ f(x) for all x in X. Similarly, the function has a global (or absolute) minimum point at x∗, if f(x∗) ≤ f(x) for all x in X. The value of the function at a maximum point is called the maximum value of the function, denoted

max

(

f

(

x

)

)

{\displaystyle \max(f(x))}

, and the value of the function at a minimum point is called the minimum value of the function, (denoted

min

(

f

(

x

)

)

{\displaystyle \min(f(x))}

for clarity). Symbolically, this can be written as follows:

x

0

∈

X

{\displaystyle x_{0}\in X}

is a global maximum point of function

f

:

X

→

R

,

{\displaystyle f:X\to \mathbb {R} ,}

if

(

∀

x

∈

X

)

f

(

x

0

)

≥

f

(

x

)

.

{\displaystyle (\forall x\in X)\,f(x_{0})\geq f(x).}

The definition of global minimum point also proceeds similarly.

If the domain X is a metric space, then f is said to have a local (or relative) maximum point at the point x∗, if there exists some ε > 0 such that f(x∗) ≥ f(x) for all x in X within distance ε of x∗.