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Inference strategies for the smoothness parameter in the Potts model
2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, 20132539
Javier Gimenez 0002 +2 more
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Smoothing the Moment Estimator of the Extreme Value Parameter
Extremes, 1999Let \(\{X_n\}\) be a sequence of independent random variables whose common distribution function \(F(X)\) belongs to the domain of attraction of an extreme value distribution \(G(x)=\exp\{-(1+\gamma x)^{-1/\gamma}\}\), \(\gamma \in R^1\). This paper focused on the moment estimator \(\gamma_{k,n}\) for an extreme value parameter \(\gamma\) based on \(K\)
Resnick, Sidney, Stărică, Cătălin
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Estimation, Prediction, and Smoothing in Discrete Parameter Systems
IEEE Transactions on Computers, 1970Deterministic and probabilistic sequential machine theory is used to solve the estimation, prediction, and smoothing problem encountered in noisy discrete parameter systems such as digital data processors and information processing systems. Using Bayes' theorem, the equations describing the ideal estimator, predictor, and smoother are developed.
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How to Select the Smoothing Parameter?
1989From the results given in the previous sections it appeared that the bandwidth h played a dominant role in the behaviour of kernel estimates for regression, density or hazard function estimation.
Lázió Györfi +3 more
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Iterative estimates for a smoothing parameter
Statistics & Probability Letters, 1995zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Smooth dependence on parameters of solutions of variational inequalities
Nonlinear Analysis: Theory, Methods & Applications, 2005The authors present a result for variational inequalities on closed convex sets in Hilbert spaces that ensures the smooth dependence of the solution with respect to a parameter running in a normed space. The approach consists in showing that, under the imposed assumptions, the variational inequality is locally equivalent to a smooth equation and then ...
Eisner, J. (Jan) +2 more
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Smoothing parameter selection for nonparametric regression using smoothing spline
2013In this paper, the smoothing parameter selection problem has been examined in respect to a smoothing spline implementation in predicting nonparametric regression models. For this purpose, a simulation study has been performed by using a program written in MATLAB.
Aydin, Dursun +2 more
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Choice of Smoothing Parameters for Direct Kernels in Discrimination
Biometrical Journal, 1991AbstractDirect kernels, due to LAUDER (1983), as an alternative to the indirect kernel method in discriminant analysis are considered. It is shown that direct kernels may be based on any kernel function known in discrete density estimation. The choice of smoothing parameters is based on general loss functions and a family of loss functions which are ...
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Kalman smoothing with persistent nuisance parameters
2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2014A. Aravkin +2 more
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A Generalized Framework for Edge-Preserving and Structure-Preserving Image Smoothing
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022Wei Liu, Michael Ng, Yinjie Lei
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