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Total monotonicity : ウィキペディア英語版
Bernstein's theorem on monotone functions
In real analysis, a branch of mathematics, Bernstein's theorem states that every real-valued function on the half-line [0, ∞) that is totally monotone is a mixture of exponential functions. In one important special case the mixture is a weighted average, or expected value.
Total monotonicity (sometimes also ''complete monotonicity'') of a function ''f'' means that ''f'' is continuous on [0, ∞), infinitely differentiable on
(0, ∞), and satisfies
:(-1)^n f(t) \geq 0
for all nonnegative integers ''n'' and for all ''t'' > 0. Another convention puts the opposite inequality in the above definition.
The "weighted average" statement can be characterized thus: there is a non-negative finite Borel measure on [0, ∞), with cumulative distribution function ''g'', such that
:f(t) = \int_0^\infty e^ \,dg(x),
the integral being a Riemann–Stieltjes integral.
Nonnegative functions whose derivative is completely monotone are called ''Bernstein functions''. Every Bernstein function has the Lévy-Khintchine representation:
:f(t) = a + b t +\int_0^\infty (1-e^)\mu(dx)
where a,b \geq 0 and \mu is a measure on the positive real half-line such that
:\int_0^\infty (1\wedge x) \mu(dx) <\infty.
In more abstract language, the theorem characterises Laplace transforms of positive Borel measures on [0,∞). In this form it is known as the Bernstein–Widder theorem, or Hausdorff–Bernstein–Widder theorem. Felix Hausdorff had earlier characterised completely monotone sequences. These are the sequences occurring in the Hausdorff moment problem.
==References==

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抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
ウィキペディアで「Bernstein's theorem on monotone functions」の詳細全文を読む



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