Moderate deviations and nonparametric inference for monotone functions
From MaRDI portal
Publication:1650077
DOI10.1214/17-AOS1583zbMath1434.60087MaRDI QIDQ1650077
Xingqiu Zhao, Jie Xiong, Fu Qing Gao
Publication date: 29 June 2018
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/euclid.aos/1525313081
large deviationsGrenander estimatorstrong approximationmoderate deviationsinterval censored dataTalagrand inequalitynonparametric MLEself-normalized limit
Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Large deviations (60F10)
Related Items (7)
Asymptotic properties for quadratic functionals of linear self-repelling diffusion process and applications ⋮ Cramér-type moderate deviations for statistics in the non-stationary Ornstein–Uhlenbeck process ⋮ Statistical inference for the intensity in a partially observed jump diffusion ⋮ Deviation inequalities and Cramér-type moderate deviations for the explosive autoregressive process ⋮ Asymptotic properties for the parameter estimation in Ornstein-Uhlenbeck process with discrete observations ⋮ Self-normalized Cramér-type moderate deviations for explosive Vasicek model ⋮ Self-normalized asymptotic properties for the parameter estimation in fractional Ornstein–Uhlenbeck process
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A law of the iterated logarithm for Grenander's estimator
- Cramér-type moderate deviations for Studentized two-sample \(U\)-statistics with applications
- Maximum smoothed likelihood estimators for the interval censoring model
- Delta method in large deviations and moderate deviations for estimators
- The limit distribution of the \(L_{\infty}\)-error of Grenander-type estimators
- Maximum smoothed likelihood estimation and smoothed maximum likelihood estimation in the current status model
- Nonparametric confidence intervals for monotone functions
- Cramér-type moderate deviation for the maximum of the periodogram with application to simultaneous tests in gene expression time series
- An extremal limit theorem for the argmax process of Brownian motion minus a parabolic drift
- Moderate deviations and large deviations for kernel density estimators
- Asymptotic normality of the \(L_1\) error of the Grenander estimator
- Sharp asymptotics for isotonic regression
- Likelihood ratio tests for monotone functions.
- Weak convergence and empirical processes. With applications to statistics
- A Cramér moderate deviation theorem for Hotelling's \(T^{2}\)-statistic with applications to global tests
- The statistical analysis of interval-censored failure time data.
- Likelihood based inference for monotone response models
- On the \(\mathbb L_p\)-error of monotonicity constrained estimators
- Nonparametric Estimation under Shape Constraints
- Self-Normalized Processes
- Score Statistics for Current Status Data: Comparisons with Likelihood Ratio and Wald Statistics
- On the Bootstrap of the Maximum Score Estimator
- Confidence Intervals for Current Status Data
- On consistency of kernel density estimators for randomly censored data: Rates holding uniformly over adaptive intervals
- New concentration inequalities in product spaces
This page was built for publication: Moderate deviations and nonparametric inference for monotone functions
