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Nonparametric regression in exponential families [PDF]
, 2010 Most results in nonparametric regression theory are developed only for the case of additive noise. In such a setting many smoothing techniques including wavelet thresholding methods have been developed and shown to be highly adaptive.
Brown, Lawrence D. +2 more
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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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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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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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Nonparametric Instrumental Regression [PDF]
SSRN Electronic Journal, 2010 Summary: The focus of this paper is the nonparametric estimation of an instrumental regression function \(\varphi\) defined by conditional moment restrictions that stem from a structural econometric model \(E[Y - \varphi (Z)|W]=0\), and involve endogenous variables \(Y\) and \(Z\) and instruments \(W\).
Darolles, Serge +3 more
openaire +4 more sources
Fourier Series Nonparametric Regression Modeling in the Case of Rainfall in West Java Province
IJID (International Journal on Informatics for Development), 2022 The Fourier series is a trigonometric polynomial that has flexibility, so it adapts effectively to the local nature of the data. This Fourier series estimator is generally used when the data used is investigated for unknown patterns and there is a ...
Anatansyah Ayomi Anandari +2 more
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Development of nonparametric geographically weighted regression using truncated spline approach [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2018 Nonparametric geographically weighted regression with truncated spline approach is a new method of statistical science. It is used to solve the problems of regression analysis of spatial data if the regression curve is unknown.
Sifriyani +3 more
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