Results 11 to 20 of about 3,817,143 (297)
New Bandwidth Selection for Kernel Quantile Estimators [PDF]
Journal of Probability and Statistics, 2012 We propose a cross-validation method suitable for smoothing of kernel quantile estimators. In particular, our proposed method selects the bandwidth parameter, which is known to play a crucial role in kernel smoothing, based on unbiased estimation of a ...
Ali Al-Kenani, Keming Yu
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Smoothing Parameter Selection in two Frameworks for Penalized Splines [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2013 SummaryThere are two popular smoothing parameter selection methods for spline smoothing. First, smoothing parameters can be estimated by minimizing criteria that approximate the average mean-squared error of the regression function estimator. Second, the maximum likelihood paradigm can be employed, under the assumption that the regression function is a
Krivobokova, Tatyana +1 more
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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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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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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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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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Acta Universitatis Lodziensis. Folia Oeconomica, 2017 Ad hoc methods in the choice of smoothing parameter in kernel density estimation, although often used in practice due to their simplicity and hence the calculated efficiency, are characterized by quite big error.
Aleksandra Katarzyna Baszczyńska
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Robust smoothing of one‐dimensional data with missing and/or outlier values
IET Signal Processing, 2021 Penalized least squares (PLS) is a popular data smoothing technique. However, existing PLS smoothing algorithms behave as low‐pass filters (LPF), and, hence, they may introduce distortions to bandpass signals.
Nasser Mourad
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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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IEEE Access, 2022 In the flexible DC grids, selections of slope coefficients in system level controls and designs of smoothing reactors have a crucial influence on the system stability.
Hui Li, Xinqiao Fan, Sijia Liu
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