Results 271 to 280 of about 423,513 (317)

THE GENERALIZED INVERSE, WITH NONLINEAR REGRESSION AND MATHEMATICAL PROGRAMMING APPLICATIONS

Decision Sciences, 1975
This paper is a tutorial exposition on the generalized inverse of a matrix with typical applications to regression analysis and mathematical programming. The exposition contains examples exhibiting geometrical motivation and related facts useful in application of the generalized inverse.
Henry P. Decell, Elric N. McHenry
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Nonlinear Regression, Quasi Likelihood, and Overdispersion in Generalized Linear Models

The American Statistician, 1998
Abstract The aim of this article is to reconsider the methods for handling of overdispersion in generalized linear models proposed by McCullagh and Nelder. Our starting point will be a nonlinear regression model with normal errors, specified by a mean function, a variance function and a matrix of covariates.
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Nonlinear regression using order statistics from the multivariate generalized hyperbolic distributions

Communications in Statistics - Simulation and Computation, 2019
In this paper, by considering an (n+1)-dimensional random vector (X1,X2,….,Xn,Y)T from the multivariate generalized hyperbolic (GH) distribution, we derive the joint distribution of Y and the order...
M. Amiri, R. Roozegar, A. Jamalizadeh
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Construction and Application of public Building Virtual Generator Based on Multiple Nonlinear Regression

2021 IEEE 11th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), 2021
As the main power consumption system of public buildings, central air-conditioning can be constructed as a virtual generator unit to participate in the operation of power system because of its flexible and adjustable characteristics. There are many electrical devices in the central air conditioning system, and the coupling relationship between the ...
Bing Wang, Lin Cong, Na Li, Nan Wang, Xichao Zhou, Jianyong Ding, Ciwei Gao   +6 more
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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.
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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
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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
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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.
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Nonlinear Spatial Patterns in Spatial Regression Models: Findings from a General Misspecification Test.

, 2006
Thomas de Graaff, C.A.G.M. van Montfort, Peter Nijkamp   +2 more
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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
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