Results 21 to 30 of about 2,308,308 (297)
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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Identifiability of logistic regression with homoscedastic error: Berkson model
Modern Stochastics: Theory and Applications, 2015 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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IEEE Transactions on Information Theory, 2018 15 pages, 3 figures ...
Xiaoqing Fan +2 more
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Polynomial Regression With Errors in the Variables
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1998 Summary A polynomial functional relationship with errors in both variables can be consistently estimated by constructing an ordinary least squares estimator for the regression coefficients, assuming hypothetically the latent true regressor variable to be known, and then adjusting for the errors. If normality of the error variables can be
Cheng, Chi-Lun, Schneeweiss, Hans
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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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Variable-Length Compression Allowing Errors [PDF]
IEEE Transactions on Information Theory, 2014 This paper studies the fundamental limits of the minimum average length of lossless and lossy variable-length compression, allowing a nonzero error probability $ε$, for lossless compression. We give non-asymptotic bounds on the minimum average length in terms of Erokhin's rate-distortion function and we use those bounds to obtain a Gaussian ...
Victoria Kostina +2 more
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Identification of Fractional Models of an Induction Motor with Errors in Variables
Fractal and Fractional, 2023 The skin effect in modeling an induction motor can be described by fractional differential equations. The existing methods for identifying the parameters of an induction motor with a rotor skin effect suggest the presence of errors only in the output ...
Dmitriy Ivanov
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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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Asymptotic normality of total least squares estimator in a multivariate errors-in-variables model
Modern Stochastics: Theory and Applications, 2016 We consider a multivariate functional measurement error model $AX\approx B$. The errors in $[A,B]$ are uncorrelated, row-wise independent, and have equal (unknown) variances.
Alexander Kukush +1 more
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On The Errors-In-Variables Model With Singular Dispersion Matrices
Journal of Geodetic Science, 2014 While the Errors-In-Variables (EIV) Model has been treated as a special case of the nonlinear Gauss- Helmert Model (GHM) for more than a century, it was only in 1980 that Golub and Van Loan showed how the Total Least-Squares (TLS) solution can be ...
Schaffrin B., Snow K., Neitzel F.
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