Results 11 to 20 of about 2,308,308 (297)
IEEE Access, 2023 In this paper a Maximum likelihood estimation algorithm for Finite Impulse Response Errors-in-Variables systems is developed. We consider that the noise-free input signal is Gaussian-mixture distributed.
Angel L. Cedeno +4 more
doaj +1 more source
Changepoint in Error-Prone Relations
Mathematics, 2021 Linear relations, containing measurement errors in input and output data, are considered. Parameters of these so-called errors-in-variables models can change at some unknown moment.
Michal Pešta
doaj +1 more source
Errors in Variables in Panel Data [PDF]
Journal of Econometrics, 1986 Abstract Panel data based studies in econometrics use the analysis of covariance approach to control for various ‘individual effects’ by estimating coefficients from the ‘within’ dimension of the data. Often, however, the results are unsatisfactory, with ‘too low’ and insignificant coefficients.
Zvi Griliches, Jerry A. Hausman
openaire +1 more source
Statistical inference for partially linear errors-in-variables panel data models with fixed effects
Systems Science & Control Engineering, 2021 In this paper, we consider the statistical inference for the partially linear panel data models with fixed effects. We focus on the case where some covariates are measured with additive errors. We propose a modified profile least squares estimator of the
Bangqiang He, Minxiu Yu, Jinming Zhou
doaj +1 more source
Estimation in a linear errors-in-variables model under a mixture of classical and Berkson errors
Modern Stochastics: Theory and Applications, 2021 A linear structural regression model is studied, where the covariate is observed with a mixture of the classical and Berkson measurement errors. Both variances of the classical and Berkson errors are assumed known.
Mykyta Yakovliev, Alexander Kukush
doaj +1 more source
An Overview of Linear Structural Models in Errors in Variables Regression
Revstat Statistical Journal, 2010 This paper aims to overview the numerous approaches that have been developed to estimate the parameters of the linear structural model. The linear structural model is an example of an errors in variables model, or measurement error model that has wide ...
Jonathan Gillard
doaj +1 more source
Testing straightness of line objects using total least squares [PDF]
Tehnika, 2017 The paper presents the adaptation (fitting) of a set of points, with an estimated two-dimensional positions, to the straight line model of the by the application of the Weighted Total Least Squares, WTLS.
Popović Jovan +4 more
doaj +1 more source
Errors in Variables in Linear Systems [PDF]
Econometrica, 1987 This paper extends the simple errors-in-variables bound to the setting of systems of equations. Both diagonal and nondiagonal measurement error covariance matrices are considered. In the nondiagonal case, the analogue of the simple errors-in-variables interval of estimates is an ellipsoid with diagonal equal to the line segment connecting the direct ...
openaire +2 more sources
Prediction of treatments effects in a biased allocation model
Revstat Statistical Journal, 2005 Robbins and Zhang [15] provide consistent estimators of multiplicative treatment effects under a biased treatment allocation scheme, and illustrate their methodology within Poisson and binomial models.
Fernando J.M. Magalhães
doaj +1 more source
On errors-in-variables estimation with unknown noise variance ratio [PDF]
, 2006 We propose an estimation method for an errors-in-variables model with unknown input and output noise variances. The main assumption that allows identifiability of the model is clustering of the data into two clusters that are distinct in a certain ...
Kukush, A. +2 more
core +1 more source