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The terms "non-decreasing" and "non-increasing" should not be confused with the (much weaker) negative qualifications "not decreasing" and "not increasing". For example, the non-monotonic function shown in figure 3 first falls, then rises, then falls again.
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 particular, a function is called non-monotone if it has the property that adding more elements to a set can decrease the value of the function. More formally, the function f {\displaystyle f} is non-monotone if there are sets S , T {\displaystyle S,T} in its domain s.t. S ⊂ T {\displaystyle S\subset T} and f ( S ) > f ( T ) {\displaystyle ...
A non-monotonic logic is a formal logic whose entailment relation is not monotonic.In other words, non-monotonic logics are devised to capture and represent defeasible inferences, i.e., a kind of inference in which reasoners draw tentative conclusions, enabling reasoners to retract their conclusion(s) based on further evidence. [1]
Then f is a non-decreasing function on [a, b], which is continuous except for jump discontinuities at x n for n ≥ 1. In the case of finitely many jump discontinuities, f is a step function. The examples above are generalised step functions; they are very special cases of what are called jump functions or saltus-functions. [8] [9]
The quantile function, Q, of a probability distribution is the inverse of its cumulative distribution function F. The derivative of the quantile function, namely the quantile density function, is yet another way of prescribing a probability distribution. It is the reciprocal of the pdf composed with the quantile function.
Any monotonic function is both quasiconvex and quasiconcave. More generally, a function which decreases up to a point and increases from that point on is quasiconvex (compare unimodality ). The floor function x ↦ ⌊ x ⌋ {\displaystyle x\mapsto \lfloor x\rfloor } is an example of a quasiconvex function that is neither convex nor continuous.
Moreover, the fact that the set of non-differentiability points for a monotone function is measure-zero implies that the rapid oscillations of Weierstrass' function are necessary to ensure that it is nowhere-differentiable. The Weierstrass function was one of the first fractals studied, although this term was not used until much later. The ...