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Least Squares Model Averaging Based on Generalized Cross Validation
Acta Mathematicae Applicatae Sinica, English Series, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Li, Xin-min +3 more
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Efficient generalized cross-validation for state space models
Biometrika, 1987The initial model considered is \(y(i)=s(i)+e(i)\), \(i=1,...,n\), where s(i) is an unobserved Gaussian signal and the e(i) are independent \(N(0,\sigma^ 2)\) and independent of s(i). The s(i) are generated by the state space model \[ (*)\quad s(i)=h(i,\theta)'x(i),\quad x(i+1)=F(i,\theta)x(i)+u(i) \] where u(i) is a sequence of q-dimensional ...
Ansley, Craig F., Kohn, Robert
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General Approximate Cross Validation for Model Selection
Proceedings of the 29th ACM International Conference on Multimedia, 2021Cross-validation (CV) is a ubiquitous model-agnostic tool for assessing the error of machine learning. However, it has high complexity due to the requirement of multiple times of learner training especially in multimedia tasks with huge amounts of data.
Bowei Zhu, Yong Liu 0018
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On Generalized Cross-Validation for Multivariate Smoothing Spline Functions
SIAM Journal on Scientific and Statistical Computing, 1987The aim of this paper is to contribute to the study of generalized cross- validation showing that it satisfied an asymptotic optimality condition and to prove that under the assumption that the knots have an asymptotic behavior defined by a cumulative distribution function with bounded density. To prove the main theorem (Th.
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Generalized Cross Validation stopping rule for Iterated Tikhonov regularization
2021 21st International Conference on Computational Science and Its Applications (ICCSA), 2021Ill-posed inverse problems arise in many fields of science and engineering. These problems are usually very sensitive to the presence of noise in the measured data. Regularization methods aim at reducing this sensitivity. Among these methods Iterated Tikhonov (IT), in both its standard and general form, has been widely investigated due to its ease of ...
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Smoothing Inversion of Fourier Series Using Generalized Cross-Validation
Results in Mathematics, 1996Let \(f\) be a 1-periodic, absolutely continuous function with \(\int_I |f'(t)|^2 dt< \infty\), where \(I=\) \([-1/2, 1/2]\). Instead of the exact Fourier coefficients of \(f\), \(\widehat f_k:= \int_I f(t) e^{- 2\pi ikt} dt\), only a finite sequence of noisy values of \(\widehat f_k\), \(\widehat y_k= \widehat f_k+ \widehat\varepsilon_k\) \((k= 0 ...
Tasche, Manfred, Weyrich, Norman
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Surface approximation by spline smoothing and generalized cross-validation
Mathematics and Computers in Simulation, 1992Abstract A technique is developed to approximate multi-dimensional surfaces based on smoothing splines. The tensor product is used to extend a one-dimensional spline basis to higher dimensions. The method of generalized cross-validation is applied to choose the smoothing parameter which is computed with the aid of the generalized singular value ...
Hongmin Lu, Frank H. Mathis
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Generalized cross‐validation as a stopping rule for the Richardson‐Lucy algorithm
International Journal of Imaging Systems and Technology, 1995AbstractThe Richardson‐Lucy (R‐L) algorithm has been widely used to restore degraded astronomical images. This algorithm is nothing more than the expectation‐maximization (EM) algorithm applied to Poisson data. The R‐L method is iterative in nature and converges to a (possibly local) maximum of the likelihood function. Unfortunately, because of the ill‐
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Generalized least squares cross‐validation in kernel density estimation
Statistica Neerlandica, 2015The kernel density estimation is a popular method in density estimation. The main issue is bandwidth selection, which is a well‐known topic and is still frustrating statisticians. A robust least squares cross‐validation bandwidth is proposed, which significantly improves the classical least squares cross‐validation bandwidth for its variability and ...
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Gcvpack – routines for generalized cross validation
Communications in Statistics - Simulation and Computation, 1987Douglas M. Bates +3 more
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