FIXED-B ASYMPTOTICS FOR THE STUDENTIZED MEAN FROM TIME SERIES WITH SHORT, LONG, OR NEGATIVE MEMORY
研究了长记忆和负记忆时间序列下样本均值的方差估计问题，采用固定带宽方法，推广了短记忆结果，并强调在构建均值置信区间时需考虑记忆特征。
This paper considers the problem of variance estimation for the sample mean in the context of long memory and negative memory time series dynamics, adopting the fixed-bandwidth approach now popular in the econometrics literature. The distribution theory generalizes the short memory results of Kiefer and Vogelsang (2005, Econometric Theory 21, 1130–1164). In particular, our results highlight the dependence on the kernel (we include flat-top kernels), whether or not the kernel is nonzero at the boundary, and, most important, whether or not the process is short memory. Simulation studies support the importance of accounting for memory in the construction of confidence intervals for the mean.