The paper proposes Metropolis adjusted Langevin and Hamiltonian Monte Carlo sampling
methods defined on the Riemann manifold to resolve the shortcomings of existing Monte …

Analyzing Stochastic Computer Models: A Review with Opportunities Page 1 Statistical
Science 2022, Vol. 37, No. 1, 64–89 https://doi.org/10.1214/21-STS822 © Institute of …

Significantly revised, the fifth edition of the most complete, accessible text now covers all
three approaches to structural equation modeling (SEM)--covariance-based SEM …

Two asymptotic frameworks, increasing domain asymptotics and infill asymptotics, have
been advanced for obtaining limiting distributions of maximum likelihood estimators of …

In this paper we explore methods for the online mapping of received radio signal strength
with mobile robots and localizing the source of the radio signal. By utilizing Gaussian …

The genotype-phenotype mapping of proteins is a fundamental question in structural
biology. In this Letter, with the analysis of a large dataset of proteins from hundreds of …

This paper presents a comprehensive review of the state-of-the-art developments in health
monitoring of marine structures. Monitoring the health of marine structures plays a key role in …

We study the spatial optimal sampling design for covariance parameter estimation. The
spatial process is modeled as a Gaussian random field and maximum likelihood (ML) is …

The purpose of our study is to numerically analyze the aerodynamic characteristics of
multiple wing sails which have three identical wing sails in a row and optimize their shape …

Bayesian optimization (BO) is a popular method for solving optimization problems involving
expensive objective functions. Although BO has been applied across various fields, its use …