Penalized quasi-likelihood estimation in partial linear models
The Annals of Statistics · 1997 · Volume 25 · Issue 3
Abstract
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.
Keywords
62G05, 62G20, asymptotic normality, penalized-likelihood, rates of convergence
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