Results 61 to 70 of about 83,537 (273)
Aggregation-cokriging for highly multivariate spatial data [PDF]
, 2017 Best linear unbiased prediction of spatially correlated multivariate random processes, often called cokriging in geostatistics, requires the solution of a large linear system based on the covariance and cross-covariance matrix of the observations.
Furrer, Reinhard, Genton, Marc G.
core
Sufficient Covariate, Propensity Variable and Doubly Robust Estimation
, 2015 Statistical causal inference from observational studies often requires adjustment for a possibly multi-dimensional variable, where dimension reduction is crucial.
A.P. Dawid +28 more
core +1 more source
Advanced Materials, EarlyView.Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu +3 more
wiley +1 more source
Small Area Shrinkage Estimation
, 2012 The need for small area estimates is increasingly felt in both the public and private sectors in order to formulate their strategic plans. It is now widely recognized that direct small area survey estimates are highly unreliable owing to large standard ...
Datta, G., Ghosh, M.
core +1 more source
Light‐Induced Entropy for Secure Vision
Advanced Materials, EarlyView.This work realized a ternary true random number generator by exploiting stochastic traps emerging within multiple junction interfaces, and quantitatively validated the generation of high‐quality random numbers. Furthermore, it successfully demonstrated diverse applications, including AI‐resilient image security, thereby providing a valuable guide for ...
Juhyung Seo +9 more
wiley +1 more source
Small Area Estimation Using a Spatio-Temporal Linear Mixed Model
Revstat Statistical Journal, 2012 In this paper it is proposed a spatio-temporal area level linear mixed model involving spatially correlated and temporally autocorrelated random effects.
Luís N. Pereira , Pedro S. Coelho
doaj +1 more source
Advanced Materials Technologies, EarlyView.Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu +8 more
wiley +1 more source
Advanced Science, EarlyView.Nuclear metabolism oscillates during cell cycle progression. Quantitative chromatome proteomics and imaging reveal phase‐specific dynamics of PIP5K1A and nuclear PIP2, linking phosphatidylinositol metabolism to histone methylation. This work identifies nuclear lipid metabolism as a previously unrecognized regulatory axis coordinating chromatin ...
Antoni Gañez‐Zapater +13 more
wiley +1 more source
A matrix approach to determine optimal predictors in a constrained linear mixed model
Open MathematicsFor a general vector of all unknown vectors in a constrained linear mixed model (CLMM), this study compared the dispersion matrices of the best linear unbiased predictors with any symmetric matrix for determining the optimality of predictors among others.
Güler Nesrin, Büyükkaya Melek Eriş
doaj +1 more source
Crop Journal, 2020 Genomic prediction (GP) has become a valuable tool for predicting the performance of selection candidates for the next breeding cycle. A vast majority of statistical linear models on which GP is based rely on the assumption of normality of the residuals ...
Paulino Pérez-Rodríguez +3 more
doaj +1 more source