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A Fast Algorithm for Errors-in-Variables Filtering
IEEE Transactions on Automatic Control, 2012This note concerns the optimal estimation of the input and output sequences of linear time-invariant errors-in-variables (EIV) processes. An efficient recursive filtering algorithm is proposed. It is an innovation-based approach that relies on the triangular decomposition of block Toeplitz matrices.
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Continuous-time errors-in-variables filtering
Proceedings of the 41st IEEE Conference on Decision and Control, 2002., 2003We consider estimation problems for a continuous-time linear system with a state disturbance and additive errors on the input and the output. The problem formulation and the estimation principle are deterministic. The derived filter is identical to the stochastic Kalman filter.
Ivan Markovsky +2 more
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Errors in Variables and Articles
Evaluation Review, 1982Quasi-experimental evaluations of manpower training may be biased when the mean value of preprogrammed earnings differs for participants and nonparticipants or when the two groups differ in the degree to which they deviate from the long-run trend of earnings. Both sources of bias are addressed in Director (1979).
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Error in Variable Conversion in Table
JAMA Surgery, 2023Crisanto M, Torres +2 more
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Errors in Variables in Econometrics
1998This article discusses the use of instrumental variables and grouping methods in the linear errors-in-variables or measurement error model. Comparisons are made between these methods, standard measurement error model methods with side conditions, least squares methods, and replicated models. It is demonstrated that there are close relationships between
Chi-Lun Cheng, John W. Ness
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Errors in Variables and Cointegration
Econometric Theory, 1995In this article it is shown how the cointegration or joint trending behavior of economic time series helps to alleviate the errors in variables problem.
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Estimation in the polynomial errors-in-variables model
Science China Mathematics, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhang, Sanguo, Chen, Xiru
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Errors in variables Models [PDF]
, 2014 the participation rate should increase with the player’s observed strength, and the ...
Philippe Février, Lionel Wilner
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Robust Estimation in the Errors-in-Variables Model
Biometrika, 1989An errors-in-variables model in linear regression is considered. The model describes data consisting of \((p+1)\)-tuples \(x_ 1,...,x_ n\) with \(x_ i=X_ i+\epsilon_ i\) and \(a_ 0'X_ i=b_ 0\), where \(X_ i\) and \(\epsilon_ i\) are nonobservable independent random vectors and \(a_ 0\) is a vector of length one. Orthogonal regression determines a and b
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