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   Articles with "nonparametric regression" as a keyword



Nonparametric regression with right‐censored covariate via conditional density function

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recommendations! Published in 2022 at "Statistics in Medicine"

DOI: 10.1002/sim.9343

Abstract: Censoring often occurs in data collection. This article, considers nonparametric regression when the covariate is censored under general settings. In contrast to censoring in the response variable in survival analysis, regression with censored covariates is… read more here.

Keywords: right censored; function; regression; nonparametric regression ... See more keywords

Comparing two nonparametric regression curves in the presence of long memory in covariates and errors

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recommendations! Published in 2019 at "Metrika"

DOI: 10.1007/s00184-019-00735-4

Abstract: This paper discusses the problem of testing the equality of two nonparametric regression functions against two-sided alternatives in the presence of long memory in the common covariate and errors. The proposed test is based on… read more here.

Keywords: nonparametric regression; two nonparametric; presence long; long memory ... See more keywords

Nonparametric regression with selectively missing covariates

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recommendations! Published in 2021 at "Journal of Econometrics"

DOI: 10.1016/j.jeconom.2020.07.050

Abstract: We consider the problem of regression with selectively observed covariates in a nonparametric framework. Our approach relies on instrumental variables that explain variation in the latent covariates but have no direct effect on selection. The… read more here.

Keywords: regression selectively; regression; income; nonparametric regression ... See more keywords

The Berry-Esseen bounds of wavelet estimator for nonparametric regression models whose errors form a linear process based on ANA sequences

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recommendations! Published in 2024 at "Journal of Statistical Computation and Simulation"

DOI: 10.1080/00949655.2024.2381495

Abstract: In this paper, we consider the nonparametric regression model $ Y_{ni}= g(t_{ni})+\varepsilon _i $ Yni=g(tni)+ϵi ( $ 1\leq i\leq n $ 1≤i≤n), where $ \varepsilon _{i}=\sum _{j=-\infty }^{\infty }a_je_{i-j} $ ϵi=∑j=−∞∞ajei−j and $ e_{i} $… read more here.

Keywords: bounds wavelet; nonparametric regression; berry esseen; esseen bounds ... See more keywords

A new Bayesian wavelet thresholding estimator of nonparametric regression

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recommendations! Published in 2017 at "Journal of Applied Statistics"

DOI: 10.1080/02664763.2016.1182130

Abstract: ABSTRACT The methods of estimation of nonparametric regression function are quite common in statistical application. In this paper, the new Bayesian wavelet thresholding estimation is considered. The new mixture prior distributions for the estimation of… read more here.

Keywords: regression; nonparametric regression; estimator; new bayesian ... See more keywords
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An application of nonparametric regression to missing data in large market surveys

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recommendations! Published in 2018 at "Journal of Applied Statistics"

DOI: 10.1080/02664763.2017.1369498

Abstract: ABSTRACT Non-response (or missing data) is often encountered in large-scale surveys. To enable the behavioural analysis of these data sets, statistical treatments are commonly applied to complete or remove these data. However, the correctness of… read more here.

Keywords: regression missing; application nonparametric; nonparametric regression; data large ... See more keywords

Adaptive nonparametric regression on finite support

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recommendations! Published in 2020 at "Communications in Statistics - Theory and Methods"

DOI: 10.1080/03610926.2020.1749855

Abstract: Abstract In this paper, we propose an adaptive nonparametric regression estimation procedure when the covariate is supported over a finite interval. Unlike the classical symmetric kernel regression, the proposed kernel estimator is based on the… read more here.

Keywords: finite support; nonparametric regression; adaptive nonparametric; regression finite ... See more keywords
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Standard Errors for Nonparametric Regression

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recommendations! Published in 2020 at "Econometric Reviews"

DOI: 10.1080/07474938.2020.1772563

Abstract: Abstract This paper proposes five pointwise consistent and asymptotic normal estimators of the asymptotic variance function of the Nadaraya-Watson kernel estimator for nonparametric regression. The proposed estimators are constructed based on the first-stage nonparametric residuals,… read more here.

Keywords: errors nonparametric; nonparametric regression; standard errors; regression ... See more keywords
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Discontinuities in robust nonparametric regression with α-mixing dependence

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recommendations! Published in 2017 at "Journal of Nonparametric Statistics"

DOI: 10.1080/10485252.2017.1303061

Abstract: ABSTRACT The main idea of the paper is to introduce a robust regression estimation method under an α-mixing dependence assumption, staying free of any parametric model restrictions while also allowing for some sudden changes in… read more here.

Keywords: robust nonparametric; regression; discontinuities robust; nonparametric regression ... See more keywords

Assessment of nonlinear dose-response relationships via nonparametric regression.

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recommendations! Published in 2023 at "Journal of biopharmaceutical statistics"

DOI: 10.1080/10543406.2023.2183505

Abstract: We propose a simple approach to assess whether a nonlinear parametric model is appropriate to depict the dose-response relationships and whether two parametric models can be applied to fit a dataset via nonparametric regression. The… read more here.

Keywords: dose response; response relationships; nonparametric regression; via nonparametric ... See more keywords

Sample Efficient Nonparametric Regression via Low-Rank Regularization

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recommendations! Published in 2024 at "Journal of Computational and Graphical Statistics"

DOI: 10.1080/10618600.2024.2414891

Abstract: Abstract Nonparametric regression suffers from curse of dimensionality, requiring a relatively large sample size for accurate estimation beyond the univariate case. In this article, we consider a simple method of dimension reduction in nonparametric regression… read more here.

Keywords: nonparametric regression; sample efficient; regression; low rank ... See more keywords