Results 11 to 20 of about 1,574 (90)
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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Variational Multiscale Nonparametric Regression: Algorithms and Implementation
Algorithms, 2020 Many modern statistically efficient methods come with tremendous computational challenges, often leading to large-scale optimisation problems. In this work, we examine such computational issues for recently developed estimation methods in nonparametric ...
Miguel del Alamo +3 more
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Universal Local Linear Kernel Estimators in Nonparametric Regression
Mathematics, 2022 New local linear estimators are proposed for a wide class of nonparametric regression models. The estimators are uniformly consistent regardless of satisfying traditional conditions of dependence of design elements.
Yuliana Linke +5 more
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Nonparametric Regression with Common Shocks
Econometrics, 2016 This paper considers a nonparametric regression model for cross-sectional data in the presence of common shocks. Common shocks are allowed to be very general in nature; they do not need to be finite dimensional with a known (small) number of factors.
Eduardo A. Souza-Rodrigues
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Nonparametric Regression Estimation for Circular Data
Proceedings, 2019 Non-parametric regression with a circular response variable and a unidimensional linear regressor is a topic which was discussed in the literature.
Andrea Meilán-Vila +3 more
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Local Linear Regression Estimator on the Boundary Correction in Nonparametric Regression Estimation
Journal of Statistical Theory and Applications (JSTA), 2020 The precision and accuracy of any estimation can inform one whether to use or not to use the estimated values. It is the crux of the matter to many if not all statisticians.
Langat Reuben Cheruiyot
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Minimally Biased Nonparametric Regression and Autoregression
Revstat Statistical Journal, 2008 A nonparametric regression estimator is introduced which adapts to the smoothness of the unknown function being estimated. This property allows the new estimator to automatically achieve minimal bias over a large class of locally smooth functions ...
Timothy L. McMurry +1 more
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A-Spline Regression for Fitting a Nonparametric Regression Function with Censored Data
Stats, 2020 This paper aims to solve the problem of fitting a nonparametric regression function with right-censored data. In general, issues of censorship in the response variable are solved by synthetic data transformation based on the Kaplan–Meier estimator in the
Ersin Yılmaz +2 more
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qgam: Bayesian Nonparametric Quantile Regression Modeling in R
Journal of Statistical Software, 2021 Generalized additive models (GAMs) are flexible non-linear regression models, which can be fitted efficiently using the approximate Bayesian methods provided by the mgcv R package.
Matteo Fasiolo +4 more
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Barekeng, 2023 This study used a biresponse nonparametric regression method with truncated spline estimation that used two response variables. Nonparametric regression method is used when the regression curve is not known for its shape and pattern.One of the ...
Ar Ruum Mia Sari +2 more
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