Results 21 to 30 of about 127,829 (293)
IEEE Access, 2021 Electrical impedance tomography (EIT) is a noninvasive functional diagnostic technique that has been successfully applied to human lung and brain. EIT reconstruction is an ill-conditioned problem: the regularization parameters establish a trade-off ...
Weirui Zhang +8 more
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Use of Two Smoothing Parameters in Penalized Spline Estimator for Bi-variate Predictor Non-parametric Regression Model [PDF]
Journal of Sciences, Islamic Republic of Iran, 2020 Penalized spline criteria involve the function of goodness of fit and penalty, which in the penalty function contains smoothing parameters. It serves to control the smoothness of the curve that works simultaneously with point knots and spline degree. The
Anna Islamiyati
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Asymptotic optimality of generalized C, cross-validation, and generalized cross-validation in regression with heteroskedastic errors [PDF]
Journal of Econometrics, 1991 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
A Weighted Generalized Maximum Entropy Estimator with a Data-driven Weight
Entropy, 2009 The method of Generalized Maximum Entropy (GME), proposed in Golan, Judge and Miller (1996), is an information-theoretic approach that is robust to multicolinearity problem.
Ximing Wu
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Procrustes cross-validation of multivariate regression models [PDF]
, 2022 A generalization of Procrustes Cross-Validation — recently introduced novel approach for validation of chemometric models — is proposed. The generalized approach is faster than its predecessor by several orders of magnitude and can be used for validation
Rodionova, Oxana +2 more
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Sensors, 2019 The sliding window technique is widely used to segment inertial sensor signals, i.e., accelerometers and gyroscopes, for activity recognition. In this technique, the sensor signals are partitioned into fix sized time windows which can be of two types: (1)
Akbar Dehghani +3 more
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Choice of Smoothing Parameter for Kernel Type Ridge Estimators in Semiparametric Regression Models
Revstat Statistical Journal, 2021 This paper concerns kernel-type ridge estimators of parameters in a semiparametric model. These estimators are a generalization of the well-known Speckman’s approach based on kernel smoothing method. The most important factor in achieving this smoothing
Ersin Yilmaz +2 more
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Spatial Regression Models for Field Trials: A Comparative Study and New Ideas
Frontiers in Plant Science, 2022 Naturally occurring variability within a study region harbors valuable information on relationships between biological variables. Yet, spatial patterns within these study areas, e.g., in field trials, violate the assumption of independence of ...
Stijn Hawinkel +5 more
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Explaining the Generalized Cross-Validation on Linear Models [PDF]
Journal of Mathematics and Statistics, 2019 Cross-Validation is a model validation method widely used by the scientific community. The Generalized Cross-Validation (GCV) is an invariant version of the usual Cross-Validation method. This generalization was obtained using the non usual theory of circulant complex matrices.
Chaves, Lucas Monteiro +3 more
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The L-Curve Criterion as a Model Selection Tool in PLS Regression
Journal of Probability and Statistics, 2019 Partial least squares (PLS) regression is an alternative to the ordinary least squares (OLS) regression, used in the presence of multicollinearity. As with any other modelling method, PLS regression requires a reliable model selection tool.
Abdelmounaim Kerkri +2 more
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