Results 11 to 20 of about 117,399 (299)
Application of the Scaling Functions to Nonparametric Regression [PDF]
Informatică economică, 2007 For estimating regression function we can use many proceedings. In this paper, we have chosen to apply scaling functions to the estimation of regression functions.
Sorin MANOLE
doaj +2 more sources
Nonparametric predictive regression [PDF]
Journal of Econometrics, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kasparis, Ioannis +5 more
openaire +7 more sources
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
openaire +2 more sources
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
doaj +1 more source
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
openaire +2 more sources
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
openaire +2 more sources
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
doaj +1 more source
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
doaj +1 more source
Nonparametric Shape-Restricted Regression [PDF]
Statistical Science, 2018 This is a survey ...
Guntuboyina, Adityanand +1 more
openaire +4 more sources
Test for Linearity in Non-Parametric Regression Models
Austrian Journal of Statistics, 2022 The problem of checking the linearity of a regression relationship is addressed. The test uses nonparametric estimation techniques. The null hypothesis is that the regression function is linear; it is tested against the non-specic alternatives hypotheses.
Khedidja Djaballah-Djeddour +1 more
doaj +3 more sources