Results 31 to 40 of about 133,952 (267)
Estimating correlated observation error statistics using an ensemble transform Kalman filter [PDF]
Tellus: Series A, Dynamic Meteorology and Oceanography, 2014 For certain observing types, such as those that are remotely sensed, the observation errors are correlated and these correlations are state- and time-dependent.
Joanne A. Waller +3 more
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Regressions with Berkson errors in covariates - a nonparametric approach [PDF]
The Annals of Statistics, 2013 This paper establishes that so-called instrumental variables enable the identification and the estimation of a fully nonparametric regression model with Berkson-type measurement error in the regressors. An estimator is proposed and proven to be consistent. Its practical performance and feasibility are investigated via Monte Carlo simulations as well as
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Logistic regression error‐in‐covariate models for longitudinal high‐dimensional covariates
Stat, 2019 We consider a logistic regression model for a binary response where part of its covariates are subject‐specific random intercepts and slopes from a large number of longitudinal covariates. These random effect covariates must be estimated from the observed data, and therefore, the model essentially involves errors in covariates.
Hyung Park, Seonjoo Lee
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Treatment effect estimation with covariate measurement error [PDF]
Journal of Econometrics, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
BATTISTIN, ERICH, CHESHER A.
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An Adaptive Fusion Attitude and Heading Measurement Method of MEMS/GNSS Based on Covariance Matching
Micromachines, 2022 Aimed at the problem of filter divergence caused by unknown noise statistical characteristics or variable noise characteristics in an MEMS/GNSS integrated navigation system in a dynamic environment, on the basis of revealing the parameter adjustment ...
Wei Sun, Peilun Sun, Jiaji Wu
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Atmosphere, 2020 An efficient regional hybrid ensemble-variational (EnVar) data assimilation method using the global-ensemble-model-augmented error covariance is proposed and preliminarily tested in this study. This method uses the global ensemble error covariance as the
Yuanbing Wang +2 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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Inverse probability weighting with error-prone covariates [PDF]
Biometrika, 2013 Inverse probability-weighted estimators are widely used in applications where data are missing due to nonresponse or censoring and in the estimation of causal effects from observational studies. Current estimators rely on ignorability assumptions for response indicators or treatment assignment and outcomes being conditional on observed covariates which
Daniel F. McCaffrey +2 more
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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
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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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