Conditional Bootstrap Methods in the Mean-Shift Model
研究了如何通过分层模拟使自助法具备条件性，并以尼罗河流量数据的均值漂移分析为例，与参数和半参数似然方法进行了比较。
Bootstrap methods are not inherently conditional, but they can be made so by appropriate stratification of the simulated samples which bootstrap produces. We show how stratification can work in a bootstrap analysis of mean-shift in Nile river flow data. The results are compared with both parametric and semiparametric likelihood analyses. The paper ends with some general remarks on conditional bootstraps.