Results 261 to 270 of about 424,647 (298)

Generalized Least Squares, Taylor Series Linearization and Fisher's Scoring in Multivariate Nonlinear Regression

Journal of the American Statistical Association, 2001
In this article, we consider a general multivariate nonlinear regression setting in which the marginal mean and variance–covariance structure share a common set of regression parameters. Estimation is carried out via iteratively reweighted generalized least squares (IRGLS) that entails repeated application of Taylor series linearization and estimated ...
Vonesh E. F, Wang H., Majumdar D.
openaire   +2 more sources

A Predictive Model of Nonlinear System Based on Generalized Regression Neural Network

2005 International Conference on Neural Networks and Brain, 2006
Generalized regression neural network (GRNN) is usually applied to the function approximation. Based on the principle of GRNN, this paper presents a method for the predictive model of nonlinear complex system. The presented algorithm is applied to the training and predicting process of the nonlinear model.
null Yibin Song, null Ying Ren
openaire   +1 more source

General Estimates of the Intrinsic Variability of Data in Nonlinear Regression Models

Journal of the American Statistical Association, 1976
Abstract A dependent variable is some unknown function of independent variables plus an error component. If the magnitude of the error could be estimated with minimal assumptions about the underlying functional dependence, then this could be used to judge goodness-of-fit and as a means of selecting a subset of the independent variables which best ...
L. Breiman, W. S. Meisel
openaire   +1 more source

Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation

Technometrics, 1970
A principal objective of this paper is to discuss a class of biased linear estimators employing generalized inverses. A second objective is to establish a unifying perspective. The paper exhibits theoretical properties shared by generalized inverse estimators, ridge estimators, and corresponding nonlinear estimation procedures. From this perspective it
openaire   +1 more source

Semiparametric Generalized Least Squares in the Multivariate Nonlinear Regression Model

Econometric Theory, 1992
Asymptotically efficient estimates for the multiple equations nonlinear regression model are obtained in the presence of heteroskedasticity of unknown form. The proposed estimator is a generalized least squares based on nonparametric nearest neighbor estimates of the conditional variance matrices. Some Monte Carlo experiments are reported.
openaire   +1 more source

A General Misspecification Test for Spatial Regression Models: Dependence, Heterogeneity, and Nonlinearity

Journal of Regional Science, 2001
There is an increasing awareness of the potentials of nonlinear modeling in regional science. This can be explained partly by the recognition of the limitations of conventional equilibrium models in complex situations, and also by the easy availability and accessibility of sophisticated computational techniques.
Thomas De Graaff, Raymond J.C.M. Florax, Peter Nijkamp, Aura Reggiani   +3 more
openaire   +1 more source

Eye Gaze Calculation Based on Nonlinear Polynomial and Generalized Regression Neural Network

2009 Fifth International Conference on Natural Computation, 2009
In this paper, we present a method of calculating the direction of the line of sight, which is based on nonlinear polynomial and generalized regression neural network, using a active infrared light source system. First of all, we get a model to map the gaze parameter to the gaze point under the circumstances of a static head with nonlinear polynomial ...
Chi Jian-nan, Zhang Chuang, Yan Yan-tao, Liu Yang, Zhang Han   +4 more
openaire   +1 more source

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