Results 11 to 20 of about 284,254 (315)

Bayesian nonparametric monotone regression

Environmetrics, 2020
AbstractIn many applications there is interest in estimating the relation between a predictor and an outcome when the relation is known to be monotone or otherwise constrained due to the physical processes involved. We consider one such application‐inferring time‐resolved aerosol concentration from a low‐cost differential pressure sensor. The objective
Ander Wilson, Jessica Tryner, Christian L'Orange, John Volckens   +3 more
openaire   +5 more sources

Test for Linearity in Non-Parametric Regression Models

Austrian Journal of Statistics, 2022
The problem of checking the linearity of a regression relationship is addressed. The test uses nonparametric estimation techniques. The null hypothesis is that the regression function is linear; it is tested against the non-specic alternatives hypotheses.
Khedidja Djaballah-Djeddour, Moussa Tazerouti   +1 more
doaj   +3 more sources

Nonparametric relative recursive regression

Dependence Modeling, 2020
In this paper, we propose the problem of estimating a regression function recursively based on the minimization of the Mean Squared Relative Error (MSRE), where outlier data are present and the response variable of the model is positive.
Slaoui Yousri, Khardani Salah
doaj   +1 more source

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, Igor Borisov, Pavel Ruzankin, Vladimir Kutsenko, Elena Yarovaya, Svetlana Shalnova   +5 more
doaj   +1 more source

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, Housen Li, Axel Munk, Frank Werner   +3 more
doaj   +1 more source

Nonparametric regression analysis [PDF]

, 2015
textNonparametric regression uses nonparametric and flexible methods in analyzing complex data with unknown regression relationships by imposing minimum assumptions on the regression function.
Malloy, Shuling Guo
core   +1 more source

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 , Ricardo Fraiman , Pamela Llop   +2 more
doaj   +1 more source

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
doaj   +1 more source

Calibration Transfer Based on Nonparametric Varying Coefficient Regression [PDF]

ACS Omega
Junwei Guo, Nuohan Zhang, Beibei Li, Yipeng Wang, Meijuan Fan, Jinxia Liu, Feng Li, Zhe Jin, Sanying Feng, Song Yang, Fuwei Xie, Cong Nie, Le Zhao, Hongbo Wang   +13 more
doaj   +2 more sources

Locally Adaptive Nonparametric Binary Regression [PDF]

, 2007
A nonparametric and locally adaptive Bayesian estimator is proposed for estimating a binary regression. Flexibility is obtained by modeling the binary regression as a mixture of probit regressions with the argument of each probit regression having a thin
Cottet, Remy, Jiang, Wenxin, Kohn, Robert, Tanner, Martin, Wood, Sally   +4 more
core   +2 more sources