On the use of nonparametric regression in assessing parametric regression models

DOI10.1006/jmps.2002.1421zbMath1023.62045OpenAlexW2088954041MaRDI QIDQ1868099

Andrew Heathcote, Scott D. Brown

Publication date: 27 April 2003

Published in: Journal of Mathematical Psychology (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/3d78746927912c505de8755fe23c6f9da48a9823

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Linear regression; mixed models (62J05) Nonparametric tolerance and confidence regions (62G15) Nonparametric statistical resampling methods (62G09) Applications of statistics to psychology (62P15)

Related Items (2)

A generalization of Piéron's law to include background intensity and latency distribution ⋮ An improved kernel regression method based on Taylor expansion

Uses Software

• KernSmooth
• sm
• bootlib

Cites Work

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• Bootstrapping and related techniques. Proceedings of an international conference, held in Trier, Germany, June 4-8, 1990
• Jackknife, bootstrap and other resampling methods in regression analysis
• Accuracy, scope, and flexibility of models
• An introduction to model selection
• Akaike's information criterion and recent developments in information complexity
• Key concepts in model selection: Performance and generalizability
• Bootstrap simultaneous error bars for nonparametric regression
• Confidence Bands for Regression Functions
• On the use of nonparametric regression for model checking
• Point estimates for probability moments

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