A Riemann–Stein kernel method
نویسندگان
چکیده
This paper proposes and studies a numerical method for approximation of posterior expectations based on interpolation with Stein reproducing kernel. Finite-sample-size bounds the error are established distributions supported compact Riemannian manifold, we relate these to kernel discrepancy (KSD). Moreover, prove in our setting that KSD is equivalent Sobolev and, doing so, completely characterise convergence-determining properties KSD. Our contribution rooted novel combination Stein’s method, theory kernels, existence regularity results partial differential equations manifold.
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ژورنال
عنوان ژورنال: Bernoulli
سال: 2022
ISSN: ['1573-9759', '1350-7265']
DOI: https://doi.org/10.3150/21-bej1415