Results 21 to 30 of about 1,663,953 (297)
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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Efficient algorithms for robust generalized cross-validation spline smoothing [PDF]
, 2010 Generalized cross-validation (GCV) is a widely used parameter selection criterion for spline smoothing, but it can give poor results if the sample size n is not sufficiently large.
Anderssen, R.S. +5 more
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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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Parameter inference in mechanistic models of cellular regulation and signalling pathways using gradient matching [PDF]
, 2012 A challenging problem in systems biology is parameter inference in mechanistic models of signalling pathways. In the present article, we investigate an approach based on gradient matching and nonparametric Bayesian modelling with Gaussian processes.
Dondelinger, F. +7 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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Automatic Smoothing Parameter Selection: A Survey [PDF]
Empirical Economics, 1988 This is a survey of recent developments in smoothing parameter selection for curve estimation. The first goal of this paper is to provide an introduction to the methods available, with discussion at both a practical and also a nontechnical level, including comparison of methods.
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