The method of sieves and minimum contrast estimators

zbMath0831.62029MaRDI QIDQ1900831

Sara van de Geer

Publication date: 13 February 1996

Published in: Mathematical Methods of Statistics (Search for Journal in Brave)

zbMATH Keywords

splinesrates of convergenceleast squaresempirical processmaximum likelihood estimatorssievesminimum contrast estimationinterval censored observationsdiverging entropy integralnon-compact parameter space

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Order statistics; empirical distribution functions (62G30)

Related Items

Statistical estimation with model selection, A local maximal inequality under uniform entropy, Rates of convergence for the maximum likelihood estimator in mixture models, A maximal inequality for continuous martingales and \(M\)-estimation in a Gaussian white noise model, A new method for estimation and model selection: \(\rho\)-estimation, On the rate of convergence of the maximum likelihood estimator in Brownian semimartingale models, Set structured global empirical risk minimizers are rate optimal in general dimensions, Least-square estimation for regression on random designs for absolutely regular observations, Smooth discrimination analysis, Asymptotic normality in mixture models, M-estimation using penalties or sieves