Errors-in-variables models

Known as: Errors-in-variables, Errors-in-variables model, Measurement error model 
In statistics, errors-in-variables models or measurement error models are regression models that account for measurement errors in the independent… (More)
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2014
2014
A method for inferring causal directions based on errors-in-variables models where both the cause variable and the effect… (More)
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2012
2012
We consider fault detection through apparent changes in the bus susceptance parameters of modern power grids. We formulate the… (More)
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2011
2011
This paper extends an L2-optimal identification method for SISO errors-in-variables models (EIVMs) to cope with a MIMO case… (More)
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2006
2006
A novel direct approach for identifying continuous-time linear dynamic errors-in-variables models is presented in this paper. The… (More)
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Highly Cited
2006
Highly Cited
2006
In an errors-in-variables (EIV) model, all the measurements are corrupted by noise. The class of EIV models with constraints… (More)
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2005
2005
For the single-input-single-output (SISO) errors-in-variables system it is assumed that the system input is an ARMA process and… (More)
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2004
2004
In linear specifications, the bias due to the presence of measurement error in a regressor can be entirely avoided when either… (More)
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2001
2001
Nonlinear regression with measurement error is important for estimation from microeconomic data. One approach to identification… (More)
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1998
1998
We deal with problems connected with the identification of linear dynamic systems in situations when inputs and outputs may be… (More)
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Highly Cited
1993
Highly Cited
1993
The effect of errors in variables in nonparametric regression estimation is examined. To account for errors in covariates… (More)
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