Results 21 to 30 of about 231,500 (249)

Endogeneity in nonparametric and semiparametric regression models [PDF]

, 2001
This paper considers the nonparametric and semiparametric methods for estimating regression models with continuous endogenous regressors. We list a number of different generalizations of the linear structural equation model, and discuss how two common ...
Blundell, R., Powell, J.L.
core   +1 more source

Adaptive Reduction of Curse of Dimensionality in Nonparametric Instrumental Variable Estimation

Mathematics
Nonparametric estimation of instrumental variable treatment effects typically builds on various nonparametric identification results. However, these estimators often face challenges from the curse of dimensionality in practice, as multi-dimensional ...
Ming-Yueh Huang, Kwun Chuen Gary Chan
doaj   +1 more source

Nonparametric Range-Based Double Smoothing Spot Volatility Estimation for Diffusion Models

Complexity, 2020
We consider nonparametric spot volatility estimation for diffusion models with discrete high frequency observations. Our estimator is carried out in two steps.
Jingwei Cai
doaj   +1 more source

Bias Adjustment for a Nonparametric Entropy Estimator

Entropy, 2013
Zhang in 2012 introduced a nonparametric estimator of Shannon’s entropy, whose bias decays exponentially fast when the alphabet is finite. We propose a methodology to estimate the bias of this estimator.
Zhiyi Zhang, Michael Grabchak
doaj   +1 more source

Semi-parametric regression: Efficiency gains from modeling the nonparametric part

, 2011
It is widely admitted that structured nonparametric modeling that circumvents the curse of dimensionality is important in nonparametric estimation. In this paper we show that the same holds for semi-parametric estimation.
Mammen, Enno, Park, Byeong U., Yu, Kyusang   +2 more
core   +1 more source

On Nonparametric Estimation of Covariogram

Austrian Journal of Statistics
The paper overviews and investigates several nonparametric methods of estimating covariograms. It provides a unified approach and notation to compare the main approaches used in applied research.
Adam Bilchouris, Andriy Olenko
doaj   +1 more source

Wind power interval prediction based on hybrid semi-cloud model and nonparametric kernel density estimation

Energy Reports, 2022
In today’s increasingly serious world energy crisis, Renewable energy such as wind energy has gradually penetrated into life. Aiming at the uncertainty of wind power and the need of a mass of sample data in nonparametric kernel density estimation, a wind
Kai Zhang, Xiaodong Yu, Shulin Liu, Xia Dong, Daoqing Li, Hongzhi Zang, Rui Xu   +6 more
doaj   +1 more source

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, Mario Francisco-Fernández, Rosa M. Crujeiras, Agnese Panzera   +3 more
doaj   +1 more source

Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer

Molecular Oncology, EarlyView.
Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson, Lyanne Delgado‐Coka, Natalia Marchenko, Luisa F. Escobar‐Hoyos, Kenneth R. Shroyer, Alisa Yurovsky, Trey Ideker, Gábor Balázsi, Thomas MacCarthy, Scott Powers   +9 more
wiley   +1 more source

Nonparametric Copula Density Estimation Methodologies

Mathematics
This paper proposes several methodologies whose objective consists of securing copula density estimates. More specifically, this aim will be achieved by differentiating bivariate least-squares polynomials fitted to Deheuvels’ empirical copulas, by making
Serge B. Provost, Yishan Zang
doaj   +1 more source