Results 31 to 40 of about 30,733 (250)

Expansion for moments of regression quantiles with applications to nonparametric testing [PDF]

Bernoulli, 2019
We discuss nonparametric tests for parametric specifications of regression quantiles. The test is based on the comparison of parametric and nonparametric fits of these quantiles. The nonparametric fit is a Nadaraya-Watson quantile smoothing estimator. An asymptotic treatment of the test statistic requires the development of new mathematical arguments ...
Mammen, Enno, Van Keilegom, Ingrid, Yu, Kyusang   +2 more
openaire   +6 more sources

Powerful nonparametric checks for quantile regression [PDF]

Journal of Statistical Planning and Inference, 2017
32 pages, 2 ...
Maistre, Samuel, Lavergne, Pascal, Patilea, Valentin   +2 more
openaire   +6 more sources

Outlier Detection using Projection Quantile Regression for Mass Spectrometry Data with Low Replication

BMC Research Notes, 2012
Background Mass spectrometry (MS) data are often generated from various biological or chemical experiments and there may exist outlying observations, which are extreme due to technical reasons.
Eo Soo-Heang, Pak Daewoo, Choi Jeea, Cho HyungJun   +3 more
doaj   +1 more source

Testing for additivity in nonparametric quantile regression [PDF]

Annals of the Institute of Statistical Mathematics, 2014
Discussion Paper / SFB 823;52 ...
Dette, Holger, Guhlich, Matthias, Neumeyer, Natalie   +2 more
openaire   +3 more sources

Nonparametric probabilistic forecasting based stochastic optimal scheduling of integrated electricity and gas systems

Frontiers in Energy Research, 2023
The volatility and sporadic availability of renewable energy create significant challenges to the optimal scheduling of integrated electricity and gas systems (IEGS).
Jinyu Chen, Dawei Chen
doaj   +1 more source

Robust nonparametric estimation via wavelet median regression [PDF]

, 2008
In this paper we develop a nonparametric regression method that is simultaneously adaptive over a wide range of function classes for the regression function and robust over a large collection of error distributions, including those that are heavy-tailed,
Brown, Lawrence D., Cai, T. Tony, Zhou, Harrison H.   +2 more
core   +3 more sources

Bayesian nonparametric quantile regression using splines

Computational Statistics & Data Analysis, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Paul A. Thompson, Yuzhi Cai, Rana Moyeed, Dominic Reeve, Julian Stander   +4 more
openaire   +3 more sources

pyStoNED: A Python Package for Convex Regression and Frontier Estimation

Journal of Statistical Software
Shape-constrained nonparametric regression is a growing area in econometrics, statistics, operations research, machine learning, and related fields.
Sheng Dai, Yu-Hsueh Fang, Chia-Yen Lee, Timo Kuosmanen   +3 more
doaj   +1 more source

The Principal Component Linear Spline Quantile Regression Model in Statistical Downscaling for Rainfall Data [PDF]

Journal of Sciences, Islamic Republic of Iran
Information regarding rainfall can be obtained from global data, namely the global climate model that can be accessed through the statistical downscaling approach.
Andi Yulianti, Anna Islamiyati, Erna Herdiani   +2 more
doaj   +1 more source

Quantile-specific heritability of plasma fibrinogen concentrations.

PLoS ONE, 2022
BackgroundFibrinogen is a moderately heritable blood protein showing different genetic effects by sex, race, smoking status, pollution exposure, and disease status.
Paul T Williams
doaj   +1 more source