Results 291 to 300 of about 599,650 (333)

Statistical Tools for Nonlinear Regression

1996
International ...
Huet, S., Bouvier, A., Gruet, M.A., Jolivet, E.   +3 more
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Heteroscedastic Nonlinear Regression Models

Communications in Statistics - Simulation and Computation, 2010
In this article, we present a generalization of the Bayesian methodology introduced by Cepeda and Gamerman (2001) for modeling variance heterogeneity in normal regression models where we have orthogonality between mean and variance parameters to the general case considering both linear and highly nonlinear regression models. Under the Bayesian paradigm,
Edilberto Cepeda Cuervo, Jorge Alberto Achcar   +1 more
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Nonstationary nonlinear quantile regression

Econometric Reviews, 2016
ABSTRACTThis study examines estimation and inference based on quantile regression for parametric nonlinear models with an integrated time series covariate. We first derive the limiting distribution of the nonlinear quantile regression estimator and then consider testing for parameter restrictions, when the regression function is specified as an ...
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Prediction Intervals in Nonlinear Regression

Biometrical Journal, 1991
AbstractBy treating the nonlinear model as if it were linear in the parameterization θ in the neighbourhood of the least squares estimate θ, we construct two‐sided nominally‐q‐prediction intervals by applying the usual linear model theory. The derivation of the truncated series expansion of the expected coverage of the prediction intervals at a ...
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Nonlinear Regression

2006
The basic idea of nonlinear regression is the same as that of linear regression, namely to relate a response to a vector of predictor variables. Nonlinear regression is characterized by the fact that the prediction equation depends nonlinearly on one or more unknown parameters.
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A Note on Spurious Nonlinear Regression

SSRN Electronic Journal, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Asymmetry of estimators in nonlinear regression

Biometrika, 1987
The distributions of estimators \({\hat \vartheta}\) of the parameter \(\vartheta\) of intrinsically nonlinear regression functions f(x,\(\vartheta)\) are unknown but even with normally distributed errors they are known to be skew. A measure of asymmetry \(\lambda\) (i) of the distribution of the i-th component \({\hat \vartheta}\)(i) of \({\hat ...
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Nonlinear regression models in biology

Proceedings of the November 30--December 1, 1965, fall joint computer conference, part I on XX - AFIPS '65 (Fall, part I), 1965
Biological processes can be considered in the abstract as a response to a set of input quantities where input and output are measured in analogy with the real numbers.
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Nonlinear Regression

Journal of Marketing Research, 1990
Raymond L. Horton, G. A. F. Seber, C. J. Wild   +2 more
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Testing a Nonlinear Regression Specification: A Nonregular Case

Journal of the American Statistical Association, 1977
A Ronald Gallant
exaly   +2 more sources