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A review of innovation-based methods to jointly estimate model and observation error covariance matrices in ensemble data assimilation
(Amer Meteorological Soc, 2020-10)
Data assimilation combines forecasts from a numerical model with observations. Most of the current data assimilation algorithms consider the model and observation error terms as additive Gaussian noise, specified by their ...
Reconstructibilidad y Observabilidad por subespacios: Aplicación a la navegación
(Institute of Electrical and Electronics Engineers, 2014)
Integrated navigation systems are viewed in the context of state observability and reconstructibility. Practical empirical measures of observability and reconstructibility are proposed based on orthogonal subspace decomposition ...
A phylogenetic approach to determining the importance of constraint on phenotypic evolution in the neotropical lizard Anolis cristatellus
(Evolutionary Ecology Ltd, 2017-01-01)
Question: Is the pattern of phenotypic divergence among populations influenced by constraint in the form of the genetic covariances among characters? Background: Quantitative genetic theory predicts that when evolutionary ...
The quantization of galilean duffin-kemmer-petiau field
(2010-06)
We study the quantization of the Galilean covariant Duffin-Kemmer-Petiau (DKP) field in a five-dimensional manifold. The quantization is performed both in the canonical and in the path-integral scenario. It is considered ...
Developmental plasticity in covariance structure of the skull: Effects of prenatal stress
(Wiley Blackwell Publishing, Inc, 2011-02)
Environmental perturbations of many kinds influence growth and development. Little is known, however, about the influence of environmental factors on the patterns of phenotypic integration observed in complex morphological ...
Forecasting conditional covariance matrices in high-dimensional time series: a general dynamic factor approach
(2019-06)
Based on a General Dynamic Factor Model with infinite-dimensional factor space, we develop a new estimation and forecasting procedures for conditional covariance matrices in high-dimensional time series. The performance ...