Online Program Home
  My Program

All Times EDT

Abstract Details

Activity Number: 289 - Recent Advances in Mathematical Statistics and Probability
Type: Contributed
Date/Time: Wednesday, August 11, 2021 : 1:30 PM to 3:20 PM
Sponsor: IMS
Abstract #318245
Title: Simultaneous confidence bands for comparing variance functions of two samples in nonparametric regression model
Author(s): Chen Zhong* and Lijian Yang
Companies: Tsinghua University and Tsinghua University
Keywords: Brownian motion; B-spline; Kernel; Oracle efficiency; Variance ratio
Abstract:

Asymptotically correct simultaneous confidence bands (SCBs) are proposed in both multiplicative and additive form to compare variance functions of two samples in the nonparametric regression model based on deterministic designs. The multiplicative SCB is based on two-step estimation of ratio of the variance functions, which is as efficient, up to order $n^{-1/2}$, as an infeasible estimator if the two mean functions are known a priori. The additive SCB, which is the log transform of the multiplicative SCB, is location and scale invariant in the sense that the width of SCB is free of the unknown mean and variance functions of both samples. Simulation experiments provide strong evidence that corroborates the asymptotic theory. The proposed SCBs are used to analyze several strata pressure data sets from the Bullianta Coal Mine in Erdos City, Inner Mongolia, China.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2021 program