A critical review of surrogate assisted robust design optimization
Robust design optimization (RDO) has been eminent, ascertaining optimal configuration of
engineering systems in presence of uncertainties. However, computational aspect of …
engineering systems in presence of uncertainties. However, computational aspect of …
Applications of spatial statistical network models to stream data
Streams and rivers host a significant portion of Earth's biodiversity and provide important
ecosystem services for human populations. Accurate information regarding the status and …
ecosystem services for human populations. Accurate information regarding the status and …
[图书][B] Handbook of spatial statistics
Assembling a collection of very prominent researchers in the field, the Handbook of Spatial
Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects …
Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects …
Springer series in statistics
The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …
[图书][B] Interpolation of spatial data: some theory for kriging
ML Stein - 2012 - books.google.com
Prediction of a random field based on observations of the random field at some set of
locations arises in mining, hydrology, atmospheric sciences, and geography. Kriging, a …
locations arises in mining, hydrology, atmospheric sciences, and geography. Kriging, a …
Design of computer experiments: space filling and beyond
L Pronzato, WG Müller - Statistics and Computing, 2012 - Springer
When setting up a computer experiment, it has become a standard practice to select the
inputs spread out uniformly across the available space. These so-called space-filling …
inputs spread out uniformly across the available space. These so-called space-filling …
A critical assessment of Kriging model variants for high-fidelity uncertainty quantification in dynamics of composite shells
This paper presents a critical comparative assessment of Kriging model variants for
surrogate based uncertainty propagation considering stochastic natural frequencies of …
surrogate based uncertainty propagation considering stochastic natural frequencies of …
Convergence of Gaussian process regression with estimated hyper-parameters and applications in Bayesian inverse problems
AL Teckentrup - SIAM/ASA Journal on Uncertainty Quantification, 2020 - SIAM
This work is concerned with the convergence of Gaussian process regression. A particular
focus is on hierarchical Gaussian process regression, where hyper-parameters appearing in …
focus is on hierarchical Gaussian process regression, where hyper-parameters appearing in …
Estimation and prediction using generalized Wendland covariance functions under fixed domain asymptotics
We study estimation and prediction of Gaussian random fields with covariance models
belonging to the generalized Wendland (GW) class, under fixed domain asymptotics. As for …
belonging to the generalized Wendland (GW) class, under fixed domain asymptotics. As for …
The role of the range parameter for estimation and prediction in geostatistics
CG Kaufman, BA Shaby - Biometrika, 2013 - academic.oup.com
Two canonical problems in geostatistics are estimating the parameters in a specified family
of stochastic process models and predicting the process at new locations. We show that …
of stochastic process models and predicting the process at new locations. We show that …