Results 111 to 120 of about 281,081 (285)
Nonparametric Censored and Truncated Regression [PDF]
The nonparametric censored regression model, with a fixed, known censoring point (normalized to zero), is y = max[0,m(x) + e], where both the regression function m(x) and the distribution of the error e are unknown. This paper provides estimators of m(x)
Arthur Lewbel, Oliver Linton
core
Testing Heteroscedasticity in Nonparametric Regression Based on Trend Analysis
Journal of Applied Mathematics, 2014 We first propose in this paper a new test method for detecting heteroscedasticity of the error term in nonparametric regression. Some simulation experiments are then conducted to evaluate the performance of the proposed methodology. A real-world data set
Si-Lian Shen +2 more
doaj +1 more source
Agribusiness, EarlyView.ABSTRACT Brazil and the United States account for more than 40% of global poultry exports, with China and South Korea among their major destination markets. This study examines price transmission and market linkages between Brazil and the United States using monthly poultry export price data from January 1990 to December 2024. It also assesses which of
Khondoker Abdul Mottaleb +2 more
wiley +1 more source
Mixture of Regression Models with Single-Index
, 2016 In this article, we propose a class of semiparametric mixture regression models with single-index. We argue that many recently proposed semiparametric/nonparametric mixture regression models can be considered special cases of the proposed model. However,
Xiang, Sijia, Yao, Weixin
core
A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction
Advanced Intelligent Discovery, EarlyView.This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai +8 more
wiley +1 more source
A method for parameter hypothesis testing in nonparametric regression with Fourier series approach. [PDF]
MethodsX, 2023 Ramli M, Budiantara IN, Ratnasari V.
europepmc +1 more source
Nonparametric Specification Testing for Nonlinear Time Series with Nonstationarity [PDF]
This paper considers a nonparametric time series regression model with a nonstationary regressor. We construct a nonparametric test for testing whether the regression is of a known parametric form indexed by a vector of unknown parameters.
Dag Tjøstheim +3 more
core
Dynamic Misspecification in Nonparametric Cointegrating Regression [PDF]
Linear cointegration is known to have the important property of invariance under temporal translation. The same property is shown not to apply for nonlinear cointegration.
Ioannis Kasparis, Peter C.B. Phillips
core +3 more sources
The Challenge of Handling Structured Missingness in Integrated Data Sources
Advanced Intelligent Discovery, EarlyView.As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson +6 more
wiley +1 more source
An Online Projection Estimator for Nonparametric Regression in Reproducing Kernel Hilbert Spaces. [PDF]
Stat Sin, 2023 Zhang T, Simon N.
europepmc +1 more source