The polynomial and the Poisson measurement error models: some further results on quasi score and corrected score estimation [PDF]
, 2005 The asymptotic covariance matrices of the corrected score, the quasi score, and the simple score estimators of a polynomial measurement error model have been derived in the literature.
Schneeweiß, Hans
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On the Approximation of Precision Matrices for Wide-Swath Altimetry
Remote SensingNew observations of ocean surface topography obtained by wide-swath satellite interferometry require new capabilities to process spatially correlated errors in order to assimilate these data into numerical models.
Max Yaremchuk +2 more
doaj +1 more source
Sampled-data filtering with error covariance assignment [PDF]
, 2001 Copyright [2001] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services.
Huang, B, Huo, P, Wang, Z
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Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization. [PDF]
PLoS ONE, 2013 Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models.
Daniel Bartz +4 more
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Covariate Balancing With Measurement Error
Statistics in MedicineABSTRACT In recent years, there is a growing body of causal inference literature focusing on covariate balancing methods. These methods eliminate observed confounding by equalizing covariate moments between the treated and control groups.
Xialing Wen, Ying Yan
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Low-dimensional representation of error covariance [PDF]
Tellus A: Dynamic Meteorology and Oceanography, 2000 Ensemble and reduced-rank approaches to prediction and assimilation rely on low-dimensionalapproximations of the estimation error covariances. Here stability properties of the forecast/analysis cycle for linear, time-independent systems are used to identify factors that cause thesteady-state analysis error covariance to admit a low-dimensional ...
Tippett, Michael K. +3 more
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Journal of Modern Power Systems and Clean Energy, 2020 Distribution state estimation (DSE) is an essential part of an active distribution network with high level of distributed energy resources. The challenges of accurate DSE with limited measurement data is a well-known problem.
Alan Louis +3 more
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SURVIVAL TIME REGRESSION INVOLVING COVARIATE MEASUREMENT ERROR [PDF]
Bulletin of informatics and cybernetics, 1995 Summary: A class of deconvolution estimators is proposed to estimate the conditional survival, conditional cumulative hazard and the regression functions when the covariate is subject to measurement error. Under appropriate conditions, it is shown that the proposed estimators are consistent, and that they converge weakly to Gaussian processes.
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Construction of non-diagonal background error covariance matrices for global chemical data assimilation [PDF]
Geoscientific Model Development, 2011 Chemical data assimilation attempts to optimally use noisy observations along with imperfect model predictions to produce a better estimate of the chemical state of the atmosphere.
K. Singh +5 more
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Variational assimilation for xenon dynamical forecasts in neutronic using advanced background error covariance matrix modelling [PDF]
, 2013 Data assimilation method consists in combining all available pieces of information about a system to obtain optimal estimates of initial states.
Argaud, Jean-Philippe +5 more
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