Stein's method has emerged as a powerful and versatile tool in probability theory for deriving error bounds in distributional approximations. Originally developed to ...

Organizing a global competition between approximation methods used for analyzing and modeling large spatial datasets enabled KAUST researchers to compare the performance of these different methods.

Approximation theory and asymptotic methods form a foundational framework that bridges classical ideas with modern numerical analysis, enabling researchers to obtain practical, near‐optimal solutions ...

SIAM Journal on Numerical Analysis, Vol. 54, No. 4 (2016), pp. 2256-2281 (26 pages) The focus of this paper is the approximation of analytic functions on compact intervals from their pointwise values ...

An important part of the marginal maximum likelihood method described previously is the computation of the integral over the random effects. The default method in PROC NLMIXED for computing this ...

This is a preview. Log in through your library . SIAM Journal on Numerical Analysis contains research articles on the development and analysis of numerical methods ...

Covers asymptotic evaluation of integrals (stationary phase and steepest descent), perturbation methods (regular and singular methods, and inner and outer expansions), multiple scale methods, and ...

Clinical trials have traditionally followed a fixed design, in which patient allocation to treatments is fixed throughout the trial and specified in the protocol. The primary goal of this static ...

A puzzle in theoretical chemistry has been solved at TU Wien: A new computational method now makes it possible to calculate the forces between large molecules with unprecedented accuracy. Why can ...