Results 121 to 130 of about 4,368 (154)

A Monte Carlo comparison of parametric and nonparametric quantile regressions

Applied Economics Letters, 2004
This study compares parametric and nonparametric quantile regression methods using Monte Carlo simulations. Simulation results indicate that the nonparametric quantile regression approach is more appropriate, particularly when the underlying model is nonlinear or the error term follows a non-normal distribution.
Insik Min, Inchul Kim
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Nonparametric Estimation of Conditional Quantile Regression with Mixed Discrete and Continuous Data

SSRN Electronic Journal, 2015
In this paper, we investigate the nonlinear quantile regression with mixed discrete and continuous regressors. A local linear smoothing technique with the mixed continuous and discrete kernel function is proposed to estimate the conditional quantile regression function.
Degui Li, Qi Li, Zheng Li
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Asymptotic properties of nonparametric estimation and quantile regression in Bayesian structural equation models

Journal of Multivariate Analysis, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kim, Gwangsu, Choi, Taeryon
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Linear and Nonparametric Quantile Regression

2012
Quantile regression estimates can be presented in tables alongside linear regression estimates. A possible advantage of this approach to presenting quantile regression results is that it is easy to compare the values of the coefficients and standard errors with OLS estimates and across quantiles. As we have seen, quantile estimates actually contain far
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Correction to “Fast Nonparametric Quantile Regression With Arbitrary Smoothing Methods” published in theJournal of Computational and Graphical Statistics, 20, 510–526

Journal of Computational and Graphical Statistics, 2011
(2011). Correction to “Fast Nonparametric Quantile Regression With Arbitrary Smoothing Methods” published in the Journal of Computational and Graphical Statistics, 20, 510–526. Journal of Computational and Graphical Statistics: Vol. 20, No. 3, pp. 787-788.
Hee-Seok Oh, Thomas C. M. Lee, Douglas W. Nychka   +2 more
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Regression modeling for nonparametric estimation of distribution and quantile functions

2002
Summary: We propose a local linear estimator of a smooth distribution function. This estimator applies local linear techniques to observations from a regression model in which the value of the empirical distribution function equals the value of the true distribution plus an error term.
Cheng, M.-Y., Peng, L.
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Generalized, quantile and constrained nonparametric regression for spatial data

The dissertation consists of three research projects to discuss some limitations in spatially varying coefficient models (SVCMs) for spatial data over complicated domains. In the first project, we introduce generalized spatially varying coefficient models (GSVCMs) to extend a class of SVCMs to investigate the effects of local features on various types ...
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Nonparametric and Semiparametric Quantile Regression via a New MM Algorithm

Journal of Computational and Graphical Statistics, 2023
Bo Kai, Mian Huang, Weixin Yao, Yuexiao Dong   +3 more
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Combining probability and non‐probability samples using semi‐parametric quantile regression and a nonparametric estimator of the participation probability

Scandinavian Journal of Statistics
Abstract Non‐probability samples are prevalent in various fields, such as biomedical studies, educational research, and business investigations, owing to the escalating challenges associated with declining response rates and the cost‐effectiveness and convenience of utilizing such samples.
Emily Berg, Sixia Chen, Cindy Yu
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RODEO for Sparse Nonparametric Regression and Quantile Regression with Censored Data

2007
RODEO is a recently developed general strategy for nonparametric estimation based on the regularization of the estimator derivatives with respect to the smoothing parameters. In the original nonparametric regression framework, RODEO results in a simple yet effective new algorithm for simultaneous bandwidth and variable selection with interesting ...
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