Results 31 to 40 of about 932 (214)
Resistant Nonparametric Smoothing with S-PLUS
Journal of Statistical Software, 2004 In this paper we introduce and illustrate the use of an S-PLUS set of functions to fit M-type smoothing splines with the smoothing parameter chosen by a robust criterion (either a robust version of cross-validation or a robust version of Mallows's Cp ...
Eva Cantoni
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Penalized spline estimator with multi smoothing parameters in bi-response multi-predictor nonparametric regression model for longitudinal data [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2020 Penalized spline estimators that depend on a smoothing parameter is one type of estimator used in the estimation regression curve in nonparametric regression.
Anna Islamiyati, Fatmawati, Nur Chamidah
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Stats, 2020 In a functional linear model (FLM) with scalar response, the parameter curve quantifies the relationship between a functional explanatory variable and a scalar response.
Eduardo L. Montoya
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Estimation of the Smoothing Parameters in the HPMV Filter
Annals of the Alexandru Ioan Cuza University - Mathematics, 2011 We suggest an optimality criterion, for choosing the best smoothing parameters for an extension of the so-called Hodrick-Prescott Multivariate (HPMV) filter. We show that this criterion admits a whole set of optimal smoothing parameters, to which belong the widely used noise-to-signal ratios.
Rahmania, Nadji +2 more
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Direct Determination of Smoothing Parameter for Penalized Spline Regression
Journal of Probability and Statistics, 2014 Penalized spline estimator is one of the useful smoothing methods. To construct the estimator, having goodness of fit and smoothness, the smoothing parameter should be appropriately selected. The purpose of this paper is to select the smoothing parameter
Takuma Yoshida
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Remote Sensing, 2020 Accurate evaluation of start of season (SOS) changes is essential to assess the ecosystem’s response to climate change. Smoothing method is an understudied factor that can lead to great uncertainties in SOS extraction, and the applicable situation for ...
Nan Li +5 more
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Unsupervised estimation of dirichlet smoothing parameters
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, 2010 A standard approach for determining a Dirichlet smoothing parameter is to choose a value which maximizes a retrieval performance metric using training data consisting of queries and relevance judgments. There are, however, situations where training data does not exist or the queries and relevance judgments do not reflect typical user information needs ...
Jangwon Seo, W. Bruce Croft
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Dynamic smoothness parameter for fast gradient methods [PDF]
Optimization Letters, 2017 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
FRANGIONI, ANTONIO +2 more
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Smooth Dependence of Topological Conjugacies on Parameters
Advanced Nonlinear Studies, 2011 Abstract For nonautonomous linear equations xʹ = A(t)x with a nonuniform exponential dichotomy, we show that under sufficiently small C 1 parameter-dependent perturbations, namely of the form xʹ = A(t)x + f (t, x, λ), the topological conjugacies in an appropriate version of ...
Barreira, Luis, Valls, Claudia
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Proceedings, 2018 Bootstrap methods are used for bandwidth selection in: (1) nonparametric kernel density estimation with dependent data (smoothed stationary bootstrap and smoothed moving blocks bootstrap), and (2) nonparametric kernel hazard rate estimation (smoothed ...
Inés Barbeito, Ricardo Cao
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