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The Banach Gaussian covariance and RKHS construction is well-defined
Statement
Assume AC. Under the hypotheses and notation of Covariance operator and reproducing-kernel Hilbert space of a Banach Gaussian, each exists as a Bochner integral; is a finite positive-semidefinite bilinear form; is its nullspace; and the induced map from the completion of to is continuous and injective. Thus the definition identifies a Hilbert space of shifts in .
Facts & Assumptions
AC is assumed for Fernique integrability and supplies HB for the dual-separation step (The Axiom of Choice, Hahn-Banach dominated extension theorem for real vector spaces, The real dominated-extension principle as an additional hypothesis over ZF).
Fernique integrability gives (Fernique integrability for a separable Banach Gaussian law).
A Borel map into a separable Banach space is strongly measurable (A Borel map into a separable Banach space is strongly measurable).
A strongly measurable Banach-valued function is Bochner integrable when the integral of its norm is finite; its integral norm is bounded by that scalar integral (Bochner integrability criterion, Bochner integral norm inequality).
Bounded linear maps commute with Bochner integration (Bounded linear maps commute with Bochner integration).
Continuous linear functionals separate points of a normed space (Relative dual norming, point separation, and recovery of the norm).
Cauchy–Schwarz bounds the product of two square-integrable real random variables (Cauchy-Schwarz for random variables).
Proof
Given: AC and a centered Borel Gaussian random element in a real separable Banach space , with as in the Definition.
For , the map is Borel as the composition of with the continuous map . It is strongly measurable by [F2], and is integrable by [F1]. Hence [F3] defines as a Bochner integral.
By [F1], for every ; Cauchy–Schwarz [F6] therefore makes finite. Applying to the Bochner integral using [F4] gives . Thus is a finite symmetric bilinear form, nonnegative on the diagonal. Again by [F6], , so implies for every ; therefore is the radical of and the quotient form is an inner product.
If , step 2.1 gives for every , so by [F5]. Conversely, if , taking in step 2.1 gives , hence . Therefore is well-defined and injective on .
By [F3] and [F6], So the map on the quotient is bounded and extends uniquely to its Hilbert completion because is complete. For every , the identity from step 2.1 extends by continuity to . If , then is orthogonal to the dense subspace , so . The extension is injective, proving all claims.
Depends on
- Covariance operator and reproducing-kernel Hilbert space of a Banach Gaussian
- Centered Borel Gaussian random element on a separable Banach space
- Fernique integrability for a separable Banach Gaussian law
- A Borel map into a separable Banach space is strongly measurable
- Bochner integrability criterion
- Bochner integral norm inequality
- Bounded linear maps commute with Bochner integration
- Relative dual norming, point separation, and recovery of the norm
- The Axiom of Choice
- Hahn-Banach dominated extension theorem for real vector spaces
- The real dominated-extension principle as an additional hypothesis over ZF
- Cauchy-Schwarz for random variables
Used by
- Borell–Sudakov–Tsirelson expansion for a Banach Gaussian law Theorem
- Cameron–Martin translation formula for a separable Banach Gaussian Theorem
- The support of a Banach Gaussian is the closure of its RKHS Theorem
Cited to discharge well-definedness by Covariance operator and reproducing-kernel Hilbert space of a Banach Gaussian.
Dependency tree · two levels
55 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- A. W. van der Vaart and J. H. van Zanten, Rates of contraction of posterior distributions based on Gaussian process priors (2008) (standard reference, not scraped)
- A. Lunardi, M. Miranda, and D. Pallara, Infinite Dimensional Analysis (standard reference, not scraped)