Time-bridge estimators of integrated variance

New recursive estimators of the time-average variance constant

Estimation of the time-average variance constant (TAVC) of a stationary process plays a fundamental role in statistical inference for the mean of a stochastic process. Wu (2009) proposed an efficient algorithm to recursively compute the TAVC with O(1) memory and computational complexity. In this paper, we propose two new recursive TAVC estimators that can compute TAVC estimate with O(1) computa...

Asymptotic Variance of Passage Time Estimators in Markov Chains

We consider the problem of estimating passage times in stochastic simulations of Markov chains+ Two types of estimator are considered for this purpose: the “simple” and the “overlapping” estimator; they are compared in terms of their asymptotic variance+ The analysis is based on the regenerative structure of the process and it is shown that when estimating the mean passage time, the simple esti...

Bridge Homogeneous Volatility Estimators

Derandomizing Variance Estimators

One may consider a discrete-event simulation as a Markov chain evolving on a suitably rich state space. One way that regenerative cycles may be constructed for general state-space Markov chains is to generate auxiliary coinflip random variables at each transition, with a regeneration occurring if the coin-flip results in a success. The regenerative cycles are therefore randomized with respect t...

Comparison of imputation variance estimators

Appropriate imputation inference requires both an unbiased imputation estimator and an unbiased variance estimator. The commonly used variance estimator, proposed by Rubin, can be biased when the imputation and analysis models are misspecified and/or incompatible. Robins and Wang proposed an alternative approach, which allows for such misspecification and incompatibility, but it is considerably...