Monotonic function

In mathematics, functions between ordered sets are monotonic (or monotone) if they preserve the given order. These functions first arose in calculus and were later generalized to the more abstract setting of order theory. Although the concepts generally agree, the two disciplines have developed a slightly different terminology. While in calculus, one often talks about functions being monotonically increasing and monotonically decreasing, order theory prefers the terms monotone and antitone or order-preserving and order-reversing, respectively.

General definition

Let

f: PQ

be a function between two sets P and Q, where each set carries a partial order (both of which we denote by ≤). In calculus one focuses on functions between subsets of the reals and the order ≤ is just the usual ordering on real numbers, but this is not essential for this definition.

The function f is monotone if, whenever xy, then f(x) ≤ f(y). Stated differently, a monotone function is one that preserves the order.

Monotonicity in calculus and analysis

In calculus, there is often no need to call upon the abstract methods of order theory. As already noted, functions are usually mappings between (subsets of) real numbers, ordered in the natural way.

Inspired by the shape of the graph of a monotone function on the reals, such functions are also called monotonically increasing (or "non-decreasing" or, less precisely, just "increasing"). Likewise, a function is called monotonically decreasing (or "non-increasing" or "decreasing") if, whenever xy, then f(x) ≥ f(y), i.e., if it reverses the order.

If the order ≤ in the definition of monotonicity is replaced by the strict order <, then one obtains a stronger requirement. A function with this property is called strictly increasing. Again, by inverting the order symbol, one finds a corresponding concept called strictly decreasing. Functions that are strictly increasing or decreasing are one-to-one (because ${\displaystyle a implies ${\displaystyle a\neq b}$).

The terms non-decreasing and non-increasing avoid any possible confusion with strictly increasing and strictly decreasing, respectively, see also strict.

Some basic applications and results

In calculus, each of the following properties of a function f : R → R implies the next:

These properties are the reason why monotonic functions are useful in technical work in analysis. Two facts about these functions are:

An important application of monotonic functions is in probability theory. If X is a random variable, its cumulative distribution function

FX(x) = Prob(Xx)

is a monotonically increasing function.

A function is unimodal if it is monotonically increasing up to some point (the mode) and then monotonically decreasing.

Monotonicity in order theory

In order theory, one does not restrict to real numbers, but one is concerned with arbitrary partially ordered sets or even with preordered sets. In these cases, the above definition of monotonicity is relevant as well. However, the terms "increasing" and "decreasing" are avoided, since they lose their appealing pictorial motivation as soon as one deals with orders that are not total. Furthermore, the strict relations < and > are of little use in many non-total orders and hence no additional terminology is introduced for them.

A monotone function is also called order-preserving. The dual notion is often called antitone, anti-monotone, or order-reversing. Hence, an antitone function f satisfies the property

xy implies f(x) ≥ f(y),

for all x and y in its domain. It is easy to see that the composite of two monotone mappings is also monotone.

A constant function is both monotone and antitone; conversely, if f is both monotone and antitone, and if the domain of f is a lattice, then f must be constant.

Monotone functions are central in order theory. They appear in most articles on the subject and examples from special applications are to be found in these places. Some notable special monotone functions are order embeddings (functions for which xy iff f(x) ≤ f(y)) and order isomorphisms (surjective order embeddings).

Monotonic logic

Monotonicity of entailment is a property of many logic systems that states that the hypotheses of any derived fact may be freely extended with additional assumptions. Any statement that was true in a logic having this property, will still be true even after adding any (consistent) new axioms. Logics with this property may be called monotonic in order to differentiate them from non-monotonic logic.

Monotonicity in voting criterion

Main article: Monotonicity criterion The concept of monotonicity, when applied to voting systems, is called the monotonicity criterion, and may be formulated:

A candidate x should not be harmed [i.e., change from being a winner to a loser] if x is raised on some ballots without changing the orders of the other candidates.

This criterion may be intuitively justified by reasoning that in any fair voting system, this must be true. It is an important property considered in Arrow's impossibility theorem.