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Robust estimation and testing for general nonlinear regression models

open access: closedApplied Mathematics and Computation, 1993
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Mohammad Tabatabai, Ioannis K. Argyros
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General Estimates of the Intrinsic Variability of Data in Nonlinear Regression Models

open access: closedJournal 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 ...
Leo Breiman, William S. Meisel
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NL: A Statistical Package for General Nonlinear Regression Problems

open access: closed, 1986
NL is a statistical package designed for nonlinear regression problems, taking into account the heteroscedasticity of variance, if any. The algorithm for the estimation of the regression parameters is adapted to the topic but it also presents possibilities for future extensions.
Sylvie Huet, Antoine Messéan
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Fitting De Wit competition models with general nonlinear regression programs

open access: closedEcological Modelling, 1988
Abstract Replacement series competition studies are frequently analyzed with specially designed computer programs. Commonly available nonlinear regression programs can be used to analyze such experiments with little loss of efficiency, if two indicator variables are added to the data.
Lawrence C. Larsen, William A. Williams
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