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June 1997 Penalized quasi-likelihood estimation in partial linear models
Enno Mammen, Sara van de Geer
Ann. Statist. 25(3): 1014-1035 (June 1997). DOI: 10.1214/aos/1069362736


Consider a partial linear model, where the expectation of a random variable Y depends on covariates $(x, z)$ through $F(\theta_0 x + m_0(z))$, with $\theta_0$ an unknown parameter, and $m_0$ an unknown function. We apply the theory of empirical processes to derive the asymptotic properties of the penalized quasi-likelihood estimator.


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Enno Mammen. Sara van de Geer. "Penalized quasi-likelihood estimation in partial linear models." Ann. Statist. 25 (3) 1014 - 1035, June 1997.


Published: June 1997
First available in Project Euclid: 20 November 2003

zbMATH: 0906.62033
MathSciNet: MR1447739
Digital Object Identifier: 10.1214/aos/1069362736

Primary: 62G05
Secondary: 62G20

Keywords: asymptotic normality , penalized-likelihood , rates of convergence

Rights: Copyright © 1997 Institute of Mathematical Statistics

Vol.25 • No. 3 • June 1997
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