Results 281 to 290 of about 423,513 (317)

Asymptotic normality in multivariate nonlinear regression and multivariate generalized linear regression models under repeated measurements with missing data

Statistics & Probability Letters, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Garren, Steven T., Peddada, Shyamal D.
openaire   +2 more sources

Consistency of M-estimates in general nonlinear regression models

2009
Nonlinear regression model with continuous time and weak dependent or long-range dependent stationary noise is considered. Strong consistency suffient conditions of M-estimates of regression parameters are obtained.
Ivanov, A.V., Orlovsky, I.V.
openaire   +1 more source

A generalized-constraint neural network model: Associating partially known relationships for nonlinear regressions☆

Information Sciences, 2009
In an attempt to enhance the neural network technique so that it can evolve from a ''black box'' tool into a semi-analytical one, we propose a novel modeling approach of imposing ''generalized constraints'' on a standard neural network. We redefine approximation problems by use of a new formalization with the aim of embedding prior knowledge explicitly
Bao-Gang Hu, Han-Bing Qu, Yong Wang, Shuang-Hong Yang   +3 more
openaire   +1 more source

High-Dimensional Analysis for Generalized Nonlinear Regression: From Asymptotics to Algorithm

Proceedings of the AAAI Conference on Artificial Intelligence
Overparameterization often leads to benign overfitting, where deep neural networks can be trained to overfit the training data but still generalize well on unseen data. However, it lacks a generalized asymptotic framework for nonlinear regressions and connections to conventional complexity notions.
Jian Li, Yong Liu, Weiping Wang
openaire   +1 more source

Maximum likelihood estimation and large-sample inference for generalized linear and nonlinear regression models

Biometrika, 1983
SUMMARY The class of generalized linear models is extended to allow for correlated observations, nonlinear models and error distributions not of the exponential family form. The extended class of models include a number of important examples, particularly of the composite transformational type.
openaire   +3 more sources

General regression neural network-based data-driven model-free predictive functional control for a class of discrete-time nonlinear systems

, 2021
Yuan Wang, Shun Li, Bin Zhang
openalex   +1 more source

Novel General Regression Neural Networks for Improving Control Accuracy of Nonlinear MIMO Discrete-Time Systems

, 2022
Ahmad Jobran Al-Mahasneh, Sreenatha G. Anavatti   +1 more
openalex   +1 more source

Nonlinear combination forecasting of measles incidence in Shenyang based on General Regression Neural Network

, 2020
Enbin Yang, Dongyu Yan, Qicheng Xu, Zhenhao Wang, Shitong Liu   +4 more
openalex   +1 more source

Nonlinear Equalizer Based on General Regression Neural Network in Coherent Optical OFDM System

, 2018
吴金达 Wu Jinda, 卢瑾 Lu Jin, 任宏亮 Ren Hongliang, 覃亚丽 Qin Yali, 郭淑琴 Guo Shuqin, 胡卫生 Hu Weisheng   +5 more
openalex   +1 more source

Nonlinear Regression: Fitting A General Polynomial‐Type Curve

, 2010
Richard A. Armstrong, Anthony C. Hilton
openalex   +1 more source