Robust sieve M-estimation with an application to dimensionality reduction
DOI10.1214/22-EJS2038zbMath1493.62155OpenAlexW4287987681MaRDI QIDQ2161188
Davide La Vecchia, Julien Bodelet
Publication date: 4 August 2022
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/journals/electronic-journal-of-statistics/volume-16/issue-2/Robust-sieve-M-estimation-with-an-application-to-dimensionality-reduction/10.1214/22-EJS2038.full
outliersdynamic factor modelfunctional magnetic resonance imagingsemiparametric modelingHuber loss function
Factor analysis and principal components; correspondence analysis (62H25) Nonparametric estimation (62G05) Robustness and adaptive procedures (parametric inference) (62F35)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Von Mises calculus for statistical functionals
- The statistical analysis of functional MRI data
- Convergence rate of sieve estimates
- Local asymptotics for polynomial spline regression
- Robust heart rate variability analysis by generalized entropy minimization
- M-estimation using penalties or sieves
- Weak convergence and empirical processes. With applications to statistics
- Asymptotic normality of the principal components of functional time series
- Robust high-dimensional factor models with applications to statistical machine learning
- Risk patterns and correlated brain activities. Multidimensional statistical analysis of fMRI data in economic decision making study
- Factor models in high-dimensional time series: A time-domain approach
- Introduction to empirical processes and semiparametric inference
- Sieve inference on possibly misspecified semi-nonparametric time series models
- Principal component analysis based on robust estimators of the covariance or correlation matrix: influence functions and efficiencies
- Robust High-Dimensional Volatility Matrix Estimation for High-Frequency Factor Model
- Time Series Modelling With Semiparametric Factor Dynamics
- Sieve estimation of Cox models with latent structures
- Estimation of High Dimensional Mean Regression in the Absence of Symmetry and Light Tail Assumptions
- Case-cohort studies with interval-censored failure time data
- Robust and consistent variable selection in high-dimensional generalized linear models
- Principal Components Analysis Based on Multivariate MM Estimators With Fast and Robust Bootstrap
This page was built for publication: Robust sieve M-estimation with an application to dimensionality reduction
