Results 31 to 40 of about 629,085 (265)
Mathematics, 2020 In regression analysis, oftentimes a linear (or linearized) Gauss-Markov Model (GMM) is used to describe the relationship between certain unknown parameters and measurements taken to learn about them.
Burkhard Schaffrin
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Open Mathematics, 2020 In this article, an errors-in-variables regression model in which the errors are negatively superadditive dependent (NSD) random variables is studied. First, the Marcinkiewicz-type strong law of large numbers for NSD random variables is established. Then,
Zhang Yu +3 more
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Nonparametric Regression with Errors in Variables
The Annals of Statistics, 1993 The effect of errors in variables in nonparametric regression estimation is examined. To account for errors in covariates, deconvolution is involved in the construction of a new class of kernel estimators. It is shown that optimal local and global rates of convergence of these kernel estimators can be characterized by the tail behavior of the ...
Fan, Jianqing, Truong, Young K.
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FEBS Letters, EarlyView.Enteropathogenic E. coli (EPEC) infects the human intestinal epithelium, resulting in severe illness and diarrhoea. In this study, we compared the infection of cancer‐derived cell lines with human organoid‐derived models of the small intestine. We observed a delayed in attachment, inflammation and cell death on primary cells, indicating that host ...
Mastura Neyazi +5 more
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The Case of the Homogeneous Errors-In-Variables Model
Journal of Geodetic Science, 2014 Recently, it has been claimed that the HomogeneousErrors-In-Variables (HEIV) Model, where the lefthandside (LHS) vector is allowed to be multiplied withan unknown scale factor, would represent a generalizationof the regular EIV-Model for which a number ...
Schaffrin B., Snow K.
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FEBS Letters, EarlyView.The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li +2 more
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Least squares regression with errors in both variables: case studies
Química Nova, 2013 Analytical curves are normally obtained from discrete data by least squares regression. The least squares regression of data involving significant error in both x and y values should not be implemented by ordinary least squares (OLS).
Elcio Cruz de Oliveira +1 more
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Errors-in-Variables Estimation with Wavelets
SSRN Electronic Journal, 2009 This paper proposes a wavelet (spectral) approach to estimate the parameters of a linear regression model where the regressand and the regressors are persistent processes and contain a measurement error. We propose a wavelet filtering approach which does not require instruments and yields unbiased estimates for the intercept and the slope parameters ...
Gençay, Ramazan, Gradojevic, Nikola
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FEBS Letters, EarlyView.We reconstituted Synechocystis glycogen synthesis in vitro from purified enzymes and showed that two GlgA isoenzymes produce glycogen with different architectures: GlgA1 yields denser, highly branched glycogen, whereas GlgA2 synthesizes longer, less‐branched chains.
Kenric Lee +3 more
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A Non-Iterative Approach to Direct Data-Driven Control Design of MIMO LTI Systems
IEEE Access, 2023 This paper proposes a non-iterative direct data-driven technique that deals with linear time-invariant (LTI) controller design by directly identifying the controller from input-output data without using plant identification.
Mohammad Abuabiah +3 more
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