Results 21 to 30 of about 101,932 (253)
Nonparametric regression with nonparametrically generated covariates [PDF]
The Annals of Statistics, 2012 Published in at http://dx.doi.org/10.1214/12-AOS995 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Mammen, Enno +2 more
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Nonparametric predictive regression [PDF]
Journal of Econometrics, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kasparis, Ioannis +5 more
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Nonparametric regression to the mean [PDF]
Proceedings of the National Academy of Sciences, 2003 Available data may reflect a true but unknown random variable of interest plus an additive error, which is a nuisance. The problem in predicting the unknown random variable arises in many applied situations where measurements are contaminated with errors; it is known as the regression-to-the-mean problem.
Müller, Hans-Georg +2 more
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Nonparametric C- and D-vine-based quantile regression
Dependence Modeling, 2022 Quantile regression is a field with steadily growing importance in statistical modeling. It is a complementary method to linear regression, since computing a range of conditional quantile functions provides more accurate modeling of the stochastic ...
Tepegjozova Marija +3 more
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Sequential Nonparametric Regression [PDF]
CoRR, 2012 We present algorithms for nonparametric regression in settings where the data are obtained sequentially. While traditional estimators select bandwidths that depend upon the sample size, for sequential data the effective sample size is dynamically changing.
Haijie Gu, John D. Lafferty
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An Algorithm of Nonparametric Quantile Regression
Journal of Statistical Theory and Practice, 2023 Extreme events, such as earthquakes, tsunamis, and market crashes, can have substantial impact on social and ecological systems. Quantile regression can be used for predicting these extreme events, making it an important problem that has applications in many fields. Estimating high conditional quantiles is a difficult problem.
Mei Ling Huang +2 more
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Nonparametric relative recursive regression
Dependence Modeling, 2020 In this paper, we propose the problem of estimating a regression function recursively based on the minimization of the Mean Squared Relative Error (MSRE), where outlier data are present and the response variable of the model is positive.
Slaoui Yousri, Khardani Salah
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Nonparametric Regression Based on Discretely Sampled Curves
Revstat Statistical Journal, 2020 In the context of nonparametric regression, we study conditions under which the consistency (and rates of convergence) of estimators built from discretely sampled curves can be derived from the consistency of estimators based on the unobserved whole ...
Liliana Forzani +2 more
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Nonparametric Shape-Restricted Regression [PDF]
Statistical Science, 2018 This is a survey ...
Guntuboyina, Adityanand +1 more
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Nonparametric Regression via StatLSSVM
Journal of Statistical Software, 2013 We present a new MATLAB toolbox under Windows and Linux for nonparametric regression estimation based on the statistical library for least squares support vector machines (StatLSSVM).
Kris De Brabanter +2 more
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