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A Novelty Temperature Compensation Model for Dual-Mass Vibration MEMS Gyroscope Based on Machine Learning and TTAO-VMD Algorithm. [PDF]
Micromachines (Basel)Tan W, Wang Y, Wang X.
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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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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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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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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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Implicit treatment of model error using inflated observation‐error covariance
Quarterly Journal of the Royal Meteorological Society, 2017Data assimilation involving imperfect dynamical models is an important topic in meteorology, oceanography and other geophysical applications. In filtering methods, the model error is compensated for by inflation. In variational data assimilation, authors usually try to estimate it, which means that all uncertainty‐loaded model inputs are included into ...
Gejadze, I., Oubanas, H., Shutyaev, V.
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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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