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Optimal errors-in-variables filtering
Automatica, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Guidorzi, Roberto +2 more
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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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2003
AbstractThis chapter analyses the standard regression model with errors in variables. It covers measurement error bias and unobserved heterogeneity bias, instrumental variable estimation with panel data. It presents estimates from Bover and Watson (2000) concerning economies of scale in a firm money demand equation.
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AbstractThis chapter analyses the standard regression model with errors in variables. It covers measurement error bias and unobserved heterogeneity bias, instrumental variable estimation with panel data. It presents estimates from Bover and Watson (2000) concerning economies of scale in a firm money demand equation.
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Identifiability of errors in variables dynamic systems
Automatica, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Aguero, Juan C., Goodwin, Graham C.
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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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The Degenerate Bounded Errors-in-Variables Model
SIAM Journal on Matrix Analysis and Applications, 2001The paper is devoted to a special case of the error-in-variable problem. It is viewed as total least squares with bounds on the uncertainty in the coefficient matrix. The chosen approach advantage is given as a motivation for further considerations. Corresponding proofs and algorithm synthesis are presented.
Chandrasekaran, S. +3 more
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Procrustes Errors-In-Variables Solutions
2019As shown in the previous chapters, given a matrix \(\mathbf {A}\) (origin) and a matrix \(\mathbf {B}\) (destination), containing the coordinates of p-points in \(\mathbb {R}^k\), classical least squares (LS) Procrustes solutions find the transformation parameters between the two point sets assuming that all random errors are confined to the ...
Fabio Crosilla +4 more
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Algorithms for optimal errors-in-variables filtering
Systems & Control Letters, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Diversi, Roberto +2 more
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Bootstrapping Errors-in-Variables Models
2000The bootstrap is a numerical technique, with solid theoretical foundations, to obtain statistical measures about the quality of an estimate by using only the available data. Performance assessment through bootstrap provides the same or better accuracy than the traditional error propagation approach, most often without requiring complex analytical ...
Bogdan Matei, Peter Meer
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Hypotheses Testing for Error-in-Variables Models
Annals of the Institute of Statistical Mathematics, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gimenez, Patricia +2 more
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