Bernstein's theorem on monotone functions

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Template:Short description In real analysis, a branch of mathematics, Bernstein's theorem, named after Sergei Bernstein, states that every real-valued function on the half-line Template:Closed-open that is completely monotone is a mixture of exponential functions or in more abstract language, that it is the Laplace transform of a positive Borel measure on Template:Closed-open. In one important special case the mixture is a weighted average, or expected value. It is also known as the Bernstein–Widder theorem or Hausdorff–Bernstein–Widder theorem.

History

The result was first proved by Bernstein in 1928,[1] and similar results were discussed by David Widder in 1931[2] who refers to Bernstein but states that "The author had completed the proof of this theorem a few months after the publication of Bernstein's paper without being aware of its existence". The most cited reference is the 1941 book by Widder called The Laplace Transform.[3][4] Later a simpler proof[5][6][7] was given by Boris Korenblum. At around the same time Gustave Choquet studied the much more general concept of monotone functions on semigroups and gave a more abstract proof[8][9][10][11][12] based on the Krein–Milman theorem. Felix Hausdorff had earlier characterised completely monotone sequences. These are the sequences occurring in the Hausdorff moment problem.

Statement of the theorem

Complete monotonicity of a function Template:Math means that Template:Math is continuous on Template:Closed-open, infinitely differentiable on Template:Open-open, and satisfies(−1)ndndtnf(t)≥0for all nonnegative integers Template:Mvar and for all Template:Math.

The "weighted average" statement can be characterized thus: there is a non-negative finite Borel measure on Template:Closed-open with cumulative distribution function Template:Math such thatf(t)=∫0∞e−txdg(x),the integral being a Riemann–Stieltjes integral.

Bernstein functions

Nonnegative functions whose derivative is completely monotone are called Bernstein functions.[11] Every Bernstein function has the Lévy–Khintchine representation:f(t)=a+bt+∫0∞(1−e−tx)μ(dx),where a,b≥0 and μ is a measure on the positive real half-line such that∫0∞(1∧x)μ(dx)<∞.

Schoenberg–Williamson theorem

The Schoenberg–Williamson theorem (also called Schoenberg's theorem on multiply monotone functions, Williamson's representation theorem) is the finite-order version of Bernstein's theorem. A k-monotone (or k-times monotone) function satisfies(−1)ndndtnf(t)≥0for0≤n≤kThe Schoenberg–Williamson theorem says that f is k-monotone on Template:Open-open if and only iff(t)=∫0∞(x−t)+k−1dμ(x)for some positive measure μ on Template:Open-open.

The proof was published by Williamson in 1956[13] but in his paper he mentions that "This formula was discovered by Schoenberg in 1940 but has remained unpublished".

Using the Taylor series of f with integral remainder, a more precise formula can be given[14]f(t)=∫0∞(1−txn)+n−1fn(x)dxwithfn(x)=(−1)nn!(nx)n+1f(n)(nx)I(x>0)where f(n)(t)=dndtnf(t) and I(x>0) is the indicator function of ℝ+∗.

Note then that if f is completely monotone then it is k-monotone for all k∈ℕ and the Post–Widder inversion formula states that fnconverge in distribution to μ and (1−txn)+n−1 converges to e−txas n goes to infinity, and we recover Bernstein's theorem.[14]

See also

References

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