Results 31 to 40 of about 204,377 (277)
Model selection and parameter estimation using the iterative smoothing method [PDF]
Journal of Cosmology and Astroparticle Physics, 2021 Abstract We compute the distribution of likelihoods from the non-parametric iterative smoothing method over a set of mock Pantheon-like type Ia supernova datasets. We use this likelihood distribution to test whether typical dark energy models are consistent with the data and to perform parameter estimation.
Koo, Hanwool +3 more
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Determining an effective short term COVID-19 prediction model in ASEAN countries
Scientific Reports, 2022 The challenge of accurately short-term forecasting demand is due to model selection and the nature of data trends. In this study, the prediction model was determined based on data patterns (trend data without seasonality) and the accuracy of prediction ...
Omar Sharif +2 more
doaj +1 more source
Empirical Functionals and Efficient Smoothing Parameter Selection
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1992 SUMMARY A striking feature of curve estimation is that the smoothing parameter ĥ 0, which minimizes the squared error of a kernel or smoothing spline estimator, is very difficult to estimate. This is manifest both in slow rates of convergence and in high variability of standard methods such as cross-validation.
Peter Hall, Iain Johnstone
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Revista Iberoamericana de Automática e Informática Industrial RIAI, 2017 In this work, a methodology is proposed for the improvement of the parameter estimation effciency of a non-linear manoeuvring model of a torpedo shaped unmanned underwater vehicle.
Elías Revestido Herrero +3 more
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Multiple smoothing parameters selection in additive regression quantiles
Statistical Modelling, 2020 We propose an iterative algorithm to select the smoothing parameters in additive quantile regression, wherein the functional forms of the covariate effects are unspecified and expressed via B-spline bases with difference penalties on the spline coefficients. The proposed algorithm relies on viewing the penalized coefficients as random effects from the
Muggeo, Vito M.R. +4 more
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Testing Symmetry of Unknown Densities via Smoothing with the Generalized Gamma Kernels
Econometrics, 2016 This paper improves a kernel-smoothed test of symmetry through combining it with a new class of asymmetric kernels called the generalized gamma kernels. It is demonstrated that the improved test statistic has a normal limit under the null of symmetry and
Masayuki Hirukawa, Mari Sakudo
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New Bandwidth Selection for Kernel Quantile Estimators
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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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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Molecular Oncology, EarlyView.This study integrates transcriptomic profiling of matched tumor and healthy tissues from 32 colorectal cancer patients with functional validation in patient‐derived organoids, revealing dysregulated metabolic programs driven by overexpressed xCT (SLC7A11) and SLC3A2, identifying an oncogenic cystine/glutamate transporter signature linked to ...
Marco Strecker +16 more
wiley +1 more source
Comparison of total variation with a motion estimation based compressed sensing approach for self-gated cardiac cine MRI in small animal studies. [PDF]
PLoS ONE, 2014 PURPOSE: Compressed sensing (CS) has been widely applied to prospective cardiac cine MRI. The aim of this work is to study the benefits obtained by including motion estimation in the CS framework for small-animal retrospective cardiac cine.
Juan F P J Abascal +4 more
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