Mixed-rates asymptotics

DOI10.1214/009053607000000668zbMath1131.62017arXiv0803.1942OpenAlexW3102884799MaRDI QIDQ2477061

Peter Radchenko

Publication date: 12 March 2008

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0803.1942

zbMATH Keywords

empirical processesM-estimatorsrates of convergencelimiting distributionnonstandard asymptoticsLasso\(k\)-meanspartial splinesShorthsingular quadratic approximation

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05) Functional limit theorems; invariance principles (60F17)

Related Items (11)

Moment convergence in regularized estimation under multiple and mixed-rates asymptotics ⋮ Gaussian quasi-information criteria for ergodic Lévy driven SDE ⋮ MFO-RIMS tandem workshop: Nonlocality in analysis, probability and statistics. Abstracts from the MFO-RIMS tandem workshop held March 20--26, 2022 ⋮ Semiparametric additive transformation model under current status data ⋮ Regularized bridge-type estimation with multiple penalties ⋮ Robust inference in nonlinear models with mixed identification strength ⋮ Efficient minimum distance estimation with multiple rates of convergence ⋮ Semiparametric \(M\)-estimation with non-smooth criterion functions ⋮ Parametric Modeling of Quantile Regression Coefficient Functions With Longitudinal Data ⋮ Variable selection and estimation for semi-parametric multiple-index models ⋮ Joint asymptotics for semi-nonparametric regression models with partially linear structure

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Cube root asymptotics
• The length of the shorth
• Strong consistency of k-means clustering
• A central limit theorem for k-means clustering
• Likelihood-based inference with singular information matrix
• Asymptotics for Lasso-type estimators.
• Weak convergence and empirical processes. With applications to statistics
• Nonlinear least-squares estimation
• Uniform Central Limit Theorems
• Asymptotic Statistics
• Estimation When a Parameter is on a Boundary
• A Statistical View of Some Chemometrics Regression Tools

This page was built for publication: Mixed-rates asymptotics