Reconstructing Spatial Localization Error Maps via Physics-Informed Tensor Completion for Passive Sensor Systems. [PDF]
Sensors (Basel)Zhang Z, Huang Z, Wang C, Jiang Q.
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VQF-Based Decoupled Navigation Architecture for High-Curvature Maneuvering of Underwater Vehicles. [PDF]
Sensors (Basel)Cui B +7 more
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RiTex: Harmonization of Radiomic Features Based on Riemannian Geometry. [PDF]
J ImagingVoitenko DA +5 more
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DISEASE MAPPING WITH ERRORS IN COVARIATES
Statistics in Medicine, 1997We describe Bayesian hierarchical-spatial models for disease mapping with imprecisely observed ecological covariates. We posit smoothing priors for both the disease submodel and the covariate submodel. We apply the models to an analysis of insulin Dependent Diabetes Mellitus incidence in Sardinia, with malaria prevalence as a covariate.
BERNARDINELLI, LUISA +3 more
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Sensitivity of analysis error covariance to the mis‐specification of background error covariance
Quarterly Journal of the Royal Meteorological Society, 2012AbstractMost data assimilation and satellite retrieval methods are based on optimal estimation theory, which assumes that the error covariances of the observations and of the a priori (background) information are known. The specification of background error covariance is crucial to the appropriate interpretation of radiance information from satellite ...
J. R. Eyre, F. I. Hilton
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Analysis of Covariance with Non‐normal Errors
International Statistical Review, 2009Summary Analysis of covariance techniques have been developed primarily for normally distributed errors. We give solutions when the errors have non‐normal distributions. We show that our solutions are efficient and robust. We provide a real‐life example.
Şenoğlu, Birdal +1 more
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Cox Regression with Covariate Measurement Error
Scandinavian Journal of Statistics, 2002This article deals with parameter estimation in the Cox proportional hazards model when covariates are measured with error. We consider both the classical additive measurement error model and a more general model which represents the mis‐measured version of the covariate as an arbitrary linear function of the true covariate plus random noise.
Hu, Chengcheng, Lin, D. Y.
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Adjusting for covariate errors with nonparametric assessment of the true covariate distribution
Biometrika, 2004Summary: A well-known and useful method for generalised regression analysis when a linear covariate \(x\) is available only through some approximation \(z\) is to carry out more or less the usual analysis with \(E(x\,|\,z)\) substituted for \(x\).
Pierce, Donald A., Kellerer, Albrecht M.
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A Longitudinal Measurement Error Model with a Semicontinuous Covariate
Biometrics, 2005Summary Covariate measurement error in regression is typically assumed to act in an additive or multiplicative manner on the true covariate value. However, such an assumption does not hold for the measurement error of sleep‐disordered breathing (SDB) in the Wisconsin Sleep Cohort Study (WSCS). The true covariate is the severity of SDB, and the observed
Li, Liang, Shao, Jun, Palta, Mari
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Covariate‐based cepstral parameterizations for time‐varying spatial error covariances
Environmetrics, 2014The difference between a mechanistic model of a spatio‐temporal process and associated observations can reasonably be represented by a random process with possible dependence structure in space and time. Often, such error processes are assumed to be stationary in time, so that a unique spatial error covariance structure is applicable for all time ...
Gladish, D. W. +2 more
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