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A monotonically non-increasing function Figure 3. A function that is not monotonic. In mathematics, a monotonic function (or monotone function) is a function between ordered sets that preserves or reverses the given order. [1] [2] [3] This concept first arose in calculus, and was later generalized to the more abstract setting of order theory.
A function that is absolutely monotonic on [,) can be extended to a function that is not only analytic on the real line but is even the restriction of an entire function to the real line. The big Bernshtein theorem : A function f ( x ) {\displaystyle f(x)} that is absolutely monotonic on ( − ∞ , 0 ] {\displaystyle (-\infty ,0]} can be ...
In more advanced mathematics the monotone convergence theorem usually refers to a fundamental result in measure theory due to Lebesgue and Beppo Levi that says that for sequences of non-negative pointwise-increasing measurable functions (), taking the integral and the supremum can be interchanged with the result being finite if either one is ...
A common example of a sigmoid function is the logistic function, ... value commonly monotonically increasing but could be decreasing. Sigmoid functions most often ...
If is a compact topological space, and () is a monotonically increasing sequence (meaning () + for all and ) of continuous real-valued functions on which converges pointwise to a continuous function :, then the convergence is uniform.
In mathematics, Helly's selection theorem (also called the Helly selection principle) states that a uniformly bounded sequence of monotone real functions admits a convergent subsequence. In other words, it is a sequential compactness theorem for the space of uniformly bounded monotone functions. It is named for the Austrian mathematician Eduard ...
The function () = = is Schur-concave, when we assume all >. In the same way, all the elementary symmetric functions are Schur-concave, when x i > 0 {\displaystyle x_{i}>0} . A natural interpretation of majorization is that if x ≻ y {\displaystyle x\succ y} then x {\displaystyle x} is less spread out than y {\displaystyle y} .
Well-known examples of convex functions of a single variable include a linear function = (where is a real number), a quadratic function (as a nonnegative real number) and an exponential function (as a nonnegative real number).