A stepwise procedure for the selection of nonlinear regression models

DOI10.1080/02331888508801822zbMath0563.62042OpenAlexW2018169543MaRDI QIDQ3676984

Helga Königsdorf, Bernd Droge

Publication date: 1985

Published in: Unnamed Author (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331888508801822

zbMATH Keywords

asymptotic resultsstepwise proceduresum of squared residualsparameter dimensionselection of nonlinear regression models

Mathematics Subject Classification ID

Software, source code, etc. for problems pertaining to statistics (62-04) Parametric hypothesis testing (62F03) Linear inference, regression (62J99) General nonlinear regression (62J02)

Related Items (1)

A note on estimating the msep in nonlinear regression

Cites Work

• Bootstrap and cross-validation estimates of the prediction error for linear regression models
• Estimating the dimension of a model
• Bootstrap methods: another look at the jackknife
• A Stepwise Variable Selection Procedure for Nonlinear Regression Models
• An optimal selection of regression variables
• Selecting Concomitant Variables Using a Likelihood Ratio Step-Down Procedure and a Method of Testing Goodness of Fit in an Exponential Survival Model
• A Step-up Procedure for Selecting Variables Associated with Survival
• Model choice and parameter estimation in regression analysis
• A new look at the statistical model identification
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