Confidence Interval Estimation for the Variance Parameter of Stationary Processes
针对严格平稳的phi混合随机过程，提出了方差参数的新渐近置信区间估计量，并与经典批均值估计量比较，证明新估计量具有更优的渐近性质。
Asymptotic confidence interval estimators of the variance parameter σ 2 = lim n → ∞ n Var((1/n) ∑ n i = 1 X i ) are described in this paper for observations X 1 , X 2 ,…,X n from a strictly stationary phi-mixing stochastic process. They are based on asymptotic properties of the standardized time series of observations from the process. The new point and interval estimators for the variance parameter are compared to the classical batch means estimator. The results show that the new estimators have asymptotic properties that clearly dominate the classical estimator. Also, asymptotic confidence interval estimators for the ratio of two variance parameters representing two independent processes are discussed.