Results 1 to 10 of about 2,287,004 (200)
Beta regression model nonlinear in the parameters with additive measurement errors in variables. [PDF]
PLoS ONE, 2021 We propose in this paper a general class of nonlinear beta regression models with measurement errors. The motivation for proposing this model arose from a real problem we shall discuss here. The application concerns a usual oil refinery process where the
Daniele de Brito Trindade +4 more
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Testing for differentially-expressed microRNAs with errors-in-variables nonparametric regression. [PDF]
PLoS ONE, 2012 MicroRNA is a set of small RNA molecules mediating gene expression at post-transcriptional/translational levels. Most of well-established high throughput discovery platforms, such as microarray, real time quantitative PCR, and sequencing, have been ...
Bin Wang +4 more
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Robust recursive estimation for the errors-in-variables nonlinear systems with impulsive noise [PDF]
Scientific ReportsThe non-Gaussian characteristic of the external disturbance poses a great challenge for system modeling and identification. This paper develops a robust recursive estimation algorithm for the errors-in-variables nonlinear system with the impulsive noise.
Xuehai Wang, Fang Zhu
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Identification of linear dynamic systems of fractional order with errors in variables based on an augmented system of equations [PDF]
Vestnik Samarskogo Gosudarstvennogo Tehničeskogo Universiteta. Seriâ: Fiziko-Matematičeskie Nauki, 2021 Equations with derivatives and fractional order differences are widely used to describe various processes and phenomena. Currently, methods of identification of systems described by equations with fractional order differences are actively developing. The
Dmitriy V. Ivanov
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Fitting an Equation to Data Impartially
Mathematics, 2023 We consider the problem of fitting a relationship (e.g., a potential scientific law) to data involving multiple variables. Ordinary (least squares) regression is not suitable for this because the estimated relationship will differ according to which ...
Chris Tofallis
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Expectile Regression With Errors-in-Variables
IEEE Access, 2023 This paper studies the expectile regression with error-in-variables to reduce the data error and describe the overall data distribution. Specifically, the asymptotic normality of the proposed estimator is thoroughly investigated, and an IRWLS algorithm ...
Xiaoxia He, Xiaodan Zhou, Chunli Li
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Regression Estimation with Errors in the Variables via the Laplace Transform
Axioms, 2023 This paper considers nonparametric regression estimation with errors in the variables. It is a standard assumption that the characteristic function of the covariate error does not vanish on the real line. This assumption is rather strong.
Huijun Guo, Qingqun Bai
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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
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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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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
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