A third order asymptotic comparison of least squares, jack-knifing and cross-validation for error variance estimation in nonlinear regression

DOI10.1080/02331888508801824zbMath0563.62040OpenAlexW2033204087MaRDI QIDQ3676982

Silvelyn Zwanzig

Publication date: 1985

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331888508801824

zbMATH Keywords

cross-validationasymptotic expansionsresidual sum of squaresprobability of concentrationmedian biascross-validatory assessmentestimators of the error variancejackknifed residual sumthird order asymptotic comparison

Mathematics Subject Classification ID

Point estimation (62F10) General nonlinear regression (62J02)

Related Items (2)

A note on estimating the msep in nonlinear regression ⋮ Asymptotic expansion for the distribution of the dispersion of the observation error in a nonlinear regression model

Cites Work

• A third-order optimum property of the maximum likelihood estimator
• Asymptotic Properties of Non-Linear Least Squares Estimators
• Unnamed Item

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