Results 11 to 20 of about 2,287,103 (299)
Statistical inference for partially linear errors-in-variables panel data models with fixed effects
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
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Prediction in polynomial errors-in-variables models
A multivariate errors-in-variables (EIV) model with an intercept term, and a polynomial EIV model are considered. Focus is made on a structural homoskedastic case, where vectors of covariates are i.i.d. and measurement errors are i.i.d. as well.
Alexander Kukush, Ivan Senko
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An Overview of Linear Structural Models in Errors in Variables Regression
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
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Estimation in a linear errors-in-variables model under a mixture of classical and Berkson errors
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
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Testing the suitability of polynomial models in errors-in-variables problems [PDF]
A low-degree polynomial model for a response curve is used commonly in practice. It generally incorporates a linear or quadratic function of the covariate.
Hall, Peter, Ma, Yanyuan
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Testing straightness of line objects using total least squares [PDF]
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
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Prediction of treatments effects in a biased allocation model
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
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Errors in Variables in Linear Systems [PDF]
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 ...
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Errors-in-variables beta regression models [PDF]
Beta regression models provide an adequate approach for modeling continuous outcomes limited to the interval (0, 1). This paper deals with an extension of beta regression models that allow for explanatory variables to be measured with error. The structural approach, in which the covariates measured with error are assumed to be random variables, is ...
Carrasco, J. +2 more
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Identifiability of logistic regression with homoscedastic error: Berkson model
We consider the Berkson model of logistic regression with Gaussian and homoscedastic error in regressor. The measurement error variance can be either known or unknown. We deal with both functional and structural cases.
Sergiy Shklyar
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