Nonparamtric bootstrapping methods may be useful for assessing confidence in a supertree inference. We examined the performance of two supertree bootstrapping methods on four published data sets that each include sequence data from more than 100 genes. In "input tree bootstrapping," input gene trees are sampled with replacement and then combined in replicate supertree analyses; in "stratified b...

We review the different block bootstrap methods for time series, and present them in a unified framework. We then revisit a recent result of Lahiri (1999b) comparing the different methods and give a corrected bound on their asymptotic relative efficiency; we also introduce a new notion of finite-sample “attainable” relative efficiency. Finally, based on the notion of spectral estimation via the...