Block bootstrap optimality and empirical block selection for sample quantiles with dependent data
TA Kuffner, SMS Lee, GA Young - Biometrika, 2021 - academic.oup.com
We establish a general theory of optimality for block bootstrap distribution estimation for
sample quantiles under mild strong mixing conditions. In contrast to existing results, we …
sample quantiles under mild strong mixing conditions. In contrast to existing results, we …
A Berry–Esseen theorem for sample quantiles under martingale difference sequences
C Lu, H Zhou, X Wang - Statistics, 2023 - Taylor & Francis
In this paper, we establish the uniformly asymptotic normality for sample quantiles based on
martingale difference sequences under some suitable conditions. We obtain the rate of …
martingale difference sequences under some suitable conditions. We obtain the rate of …
SELECTION OF PREDICTION MODELS BASED ON POSSIBILITY FUNCTION OF BINARY CONNECTION NUMBERS
H Zhou, H Chen - Advances and Applications in Statistics, 2024 - pphmjopenaccess.com
Choice of a suitable prediction model is conducive to improve the efficiency of prediction,
while the selection of prediction models can be regarded as a problem of ranking predictive …
while the selection of prediction models can be regarded as a problem of ranking predictive …
Optimal hybrid block bootstrap for sample quantiles under weak dependence
We establish a general theory of optimality for block bootstrap distribution estimation for
sample quantiles under a mild strong mixing assumption. In contrast to existing results, we …
sample quantiles under a mild strong mixing assumption. In contrast to existing results, we …