Results 21 to 30 of about 601,288 (278)
Testing the suitability of polynomial models in errors-in-variables problems [PDF]
, 2007 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]
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
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Regression quantiles with errors-in-variables [PDF]
Journal of Nonparametric Statistics, 2009 Abstract In a lot of situations, variables are measured with errors. While this problem has been previously studied in the context of kernel regression, no work has been done in quantile regression. To estimate this function, we use deconvolution kernel estimators.
Ioannides Dimitri, A. +1 more
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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
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Solution for a time-series AR model based on robust TLS estimation
Geomatics, Natural Hazards & Risk, 2019 We discuss an algorithm for the autoregression (AR) model as a typical time-series model. By analyzing the structure of the AR model, we highlight the shortcomings of traditional algorithms for model parameter estimation and propose an approach to ...
Yeqing Tao, Qiaoning He, Yifei Yao
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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
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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 ...
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Errors-in-Variables Models [PDF]
, 2000 Errors-in-variables (EIV) models axe regression models in which the regres-sors axe observed with errors. These models include the linear EIV models, the nonlinear EIV models, and the partially linear EIV models. Suppose that we want to investigate the relationship between the yield (Y) of corn and available nitrogen (X) in the soil.
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Empirical Likelihood Confidence Region for Parameters in Semi-linear Errors-in-Variables Models [PDF]
, 2006 This paper proposes a constrained empirical likelihood confidence region for a parameter in the semi-linear errors-in-variables model. The confidence region is constructed by combining the score function corresponding to the squared orthogonal distance
Cui, Hengjian, Kong, Efang
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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
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