Covariance eigenpairs neighbour distance for fault detection in chemical processes
Sign Up to like & getrecommendations! Published in 2018 at "Canadian Journal of Chemical Engineering"
DOI: 10.1002/cjce.22920
Abstract: This paper presents a new data-driven fault detection method called covariance eigenpairs neighbor distance (CEND) for monitoring chemical processes. It processes measured data in one-step sliding windows to estimate covariance, and the eigenpairs of each… read more here.
Keywords: fault; detection; covariance eigenpairs; distance ... See more keywords
Incorporating covariate information in the covariance structure of misaligned spatial data
Sign Up to like & getrecommendations! Published in 2020 at "Environmetrics"
DOI: 10.1002/env.2623
Abstract: Incorporating covariates in the second‐ structure of spatial processes is an effective way of building flexible nonstationary covariance models. Fitting these covariances requires covariates to already exist at locations where there is response data. However,… read more here.
Keywords: covariance structure; response data; structure; covariate ... See more keywords
Random fields on the hypertorus: Covariance modeling and applications
Sign Up to like & getrecommendations! Published in 2021 at "Environmetrics"
DOI: 10.1002/env.2701
Abstract: This article gives a comprehensive theoretical framework to the modeling, inference, and applications of Gaussian random fields using what we term the hypertorus as an index set. The hypertorus is obtained through a product of… read more here.
Keywords: hypertorus covariance; random fields; seasonality; covariance ... See more keywords
On the impact of spatial covariance matrix ordering on tile low‐rank estimation of Matérn parameters
Sign Up to like & getrecommendations! Published in 2024 at "Environmetrics"
DOI: 10.1002/env.2868
Abstract: Spatial statistical modeling involves processing an n×n$$ n\times n $$ symmetric positive definite covariance matrix, where n$$ n $$ denotes the number of locations. However, when n$$ n $$ is large, processing this covariance matrix… read more here.
Keywords: covariance matrix; tile low; covariance; approximation ... See more keywords
Associations of white matter hyperintensities with networks of gray matter blood flow and volume in midlife adults: A coronary artery risk development in young adults magnetic resonance imaging substudy.
Sign Up to like & getrecommendations! Published in 2022 at "Human brain mapping"
DOI: 10.1002/hbm.25876
Abstract: White matter hyperintensities (WMHs) are emblematic of cerebral small vessel disease, yet effects on the brain have not been well characterized at midlife. Here, we investigated whether WMH volume is associated with brain network alterations… read more here.
Keywords: cbf gmv; gray matter; covariance; volume ... See more keywords
A cautionary tale on the effects of different covariance structures in linear mixed effects modeling of fMRI data
Sign Up to like & getrecommendations! Published in 2024 at "Human Brain Mapping"
DOI: 10.1002/hbm.26699
Abstract: With the steadily increasing abundance of longitudinal neuroimaging studies with large sample sizes and multiple repeated measures, questions arise regarding the appropriate modeling of variance and covariance. The current study examined the influence of standard… read more here.
Keywords: variance covariance; fmri; structures linear; covariance ... See more keywords
Matching, induction, and covariance with mixed response-contingent food and noncontingent food.
Sign Up to like & getrecommendations! Published in 2021 at "Journal of the experimental analysis of behavior"
DOI: 10.1002/jeab.689
Abstract: The multiscale molar view of behavior is based on three basic laws of behavior: the Law of Allocation, the Law of Induction, and the Law of Covariance. Experiments that mix response-contingent food with noncontingent food… read more here.
Keywords: response contingent; noncontingent food; food; covariance ... See more keywords
The impact of using reconditioned correlated observation‐error covariance matrices in the Met Office 1D‐Var system
Sign Up to like & getrecommendations! Published in 2020 at "Quarterly Journal of the Royal Meteorological Society"
DOI: 10.1002/qj.3741
Abstract: Recent developments in numerical weather prediction have led to the use of correlated observation‐error covariance (OEC) information in data assimilation and forecasting systems. However, diagnosed OEC matrices are often ill‐conditioned and may cause convergence problems… read more here.
Keywords: system; convergence; oec matrix; correlated observation ... See more keywords
Background error statistics in the Tropics: Structures and impact in a convective‐scale numerical weather prediction system
Sign Up to like & getrecommendations! Published in 2020 at "Quarterly Journal of the Royal Meteorological Society"
DOI: 10.1002/qj.3785
Abstract: The background error covariance matrix plays a vital role in any data assimilation system. Proper specification, which is determined by the forecast system set‐up, is often required. Previous studies have investigated its relevance in various… read more here.
Keywords: system; background error; convective scale; covariance ... See more keywords
Why does EnKF suffer from analysis overconfidence? An insight into exploiting the ever‐increasing volume of observations
Sign Up to like & getrecommendations! Published in 2021 at "Quarterly Journal of the Royal Meteorological Society"
DOI: 10.1002/qj.3970
Abstract: Ensemble Kalman filters (EnKF) are empirically known to suffer from insufficient posterior spread and this issue is aggravated when assimilating a large volume of observations. This problem, commonly called analysis underdispersion or analysis overconfidence, has… read more here.
Keywords: analysis overconfidence; analysis; covariance; volume observations ... See more keywords
Decentralized adaptive control of large‐scale time‐varying stochastic nonlinear systems with unknown covariance
Sign Up to like & getrecommendations! Published in 2024 at "International Journal of Robust and Nonlinear Control"
DOI: 10.1002/rnc.7461
Abstract: In this paper, a novel decentralized adaptive state‐feedback design method is proposed for large‐scale stochastic nonlinear systems. Different from the existing results, we consider more practical and more general systems, that is, systems with both… read more here.
Keywords: stochastic nonlinear; decentralized adaptive; covariance; time varying ... See more keywords