Results 61 to 70 of about 489,537 (279)
Continuous canonical correlation analysis [PDF]
, 2005 Given a bivariate distribution, the set of canonical correlations and functions is in general finite or countable. By using an inner product between two functions via an extension of the covariance, we find all the canonical correlations and functions
Caudras, C.M.
core
Recovering covariance from functional fragments [PDF]
Biometrika, 2018 Biometrika, in ...
Descary, M-H, Panaretos, V M
openaire +3 more sources
Arthritis Care &Research, EarlyView.Objective Hydroxychloroquine (HCQ) is a cornerstone therapy in systemic lupus erythematosus (SLE), but the weight‐based dosing does not account for clinical factors that can introduce individual variability in drug metabolism and clearance. We leveraged longitudinal data from a prospective SLE cohort to identify clinical factors that predict ...
Jay J. Patel +6 more
wiley +1 more source
covatest: An R Package for Selecting a Class of Space-Time Covariance Functions
Journal of Statistical Software, 2020 Although a very rich list of classes of space-time covariance functions exists, specific tools for selecting the appropriate class for a given data set are needed. Thus, the main topic of this paper is to present the new R package, covatest, which can be
Claudia Cappello +2 more
doaj +1 more source
Local functional principal component analysis
, 2007 Covariance operators of random functions are crucial tools to study the way random elements concentrate over their support. The principal component analysis of a random function X is well-known from a theoretical viewpoint and extensively used in ...
Mas, André
core +2 more sources
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
A finite-difference method for linearization in nonlinear estimation algorithms [PDF]
Modeling, Identification and Control, 1998 Linearizations of nonlinear functions that are based on Jacobian matrices often cannot be applied in practical applications of nonlinear estimation techniques. An alternative linearization method is presented in this paper.
Tor S. Schei
doaj +1 more source
Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones
Advanced Engineering Materials, EarlyView.A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell +3 more
wiley +1 more source
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Geodesy and Geodynamics, 2013 When the computational point is approaching the poles, the variance and covariance formulae of the disturbing gravity gradient tensors tend to be infinite, and this is a singular problem.
Liu Xiaogang +3 more
doaj +1 more source