Results 11 to 20 of about 147,262 (309)
On Analysis Error Covariances in Variational Data Assimilation [PDF]
SIAM Journal on Scientific Computing, 2008 The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find the initial condition function (analysis). The equation for the analysis error is derived through the errors of the input data (background and observation errors).
Gejadze, Igor +2 more
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Impact of different estimations of the background-error covariance matrix on climate reconstructions based on data assimilation [PDF]
Climate of the Past, 2019 Data assimilation has been adapted in paleoclimatology to reconstruct past climate states. A key component of some assimilation systems is the background-error covariance matrix, which controls how the information from observations spreads into the model
V. Valler +5 more
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Analysis error covarianceversusposterior covariance in variational data assimilation [PDF]
Quarterly Journal of the Royal Meteorological Society, 2012 AbstractThe problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find the initial condition function (analysis). The data contain errors (observation and background errors); hence there is an error in the analysis.
Gejadze, Igor +2 more
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Cox Regression with Dependent Error in Covariates [PDF]
Biometrics, 2017 SummaryMany survival studies have error-contaminated covariates due to the lack of a gold standard of measurement. Furthermore, the error distribution can depend on the true covariates but the structure may be difficult to characterize; heteroscedasticity is a common manifestation.
Yijian Huang, Ching-Yun Wang
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Covariate Measurement Error in Logistic Regression. [PDF]
The Annals of Statistics, 1985 In a logistic regression model when covariates are subject to measurement error the naive estimator, obtained by regressing on the observed covariates, is asymptotically biased. We introduce a bias-adjusted estimator and two estimators appropriate for normally distributed measurement errors - a functional maximum likelihood estimator and an estimator ...
Stefanski, Leonard A. +1 more
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New perspectives on covariant quantum error correction [PDF]
Quantum, 2021 Covariant codes are quantum codes such that a symmetry transformation on the logical system could be realized by a symmetry transformation on the physical system, usually with limited capability of performing quantum error correction (an important case being the Eastin–Knill theorem).
Sisi Zhou, Zi-Wen Liu, Liang Jiang
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Generalized background error covariance matrix model (GEN_BE v2.0) [PDF]
Geoscientific Model Development, 2015 The specification of state background error statistics is a key component of data assimilation since it affects the impact observations will have on the analysis.
G. Descombes +4 more
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An estimate of the inflation factor and analysis sensitivity in the ensemble Kalman filter [PDF]
Nonlinear Processes in Geophysics, 2017 The ensemble Kalman filter (EnKF) is a widely used ensemble-based assimilation method, which estimates the forecast error covariance matrix using a Monte Carlo approach that involves an ensemble of short-term forecasts.
G. Wu, G. Wu, X. Zheng
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The Effect of Spatially Correlated Errors on Sea Surface Height Retrieval from SWOT Altimetry
Remote Sensing, 2023 The upcoming technology of wide-swath altimetry from space will enable monitoring the ocean surface at 4–5 times better spatial resolution and 2–3 times better accuracy than traditional nadir altimeters. This development will provide a chance to directly
Max Yaremchuk +4 more
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Accounting for Transport Error in Inversions: An Urban Synthetic Data Experiment
Earth and Space Science, 2021 We present and discuss the use of a high‐dimensional computational method for atmospheric inversions that incorporates the space‐time structure of transport and dispersion errors.
Subhomoy Ghosh +3 more
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