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PoolingAdjacentViolators and the Cauchy Mean Value Property
The Asymptotic Distribution of a Slope of Convex Minorant
Weak Convergence of SmoothlyWeighted Sums of Order Statistics
3 other sections not shown
2N+l A U B A2 implies applied assumed assumptions of Theorem asymptotic distribution asymptotic normality behavior bounded Brunk's Cauchy mean value Chapter CM CM CM CMV function combinations of order constant converges in probability converges to zero corresponding cumulative distribution function cumulative sums denote Donsker's Theorem empirical distribution function equation finite function F g is CMV Gn(u greatest convex minorant Holder condition holds identically distributed inequality integral isotonic estimator isotonic regression isotonized mean iteration IV.l Lemma III.l lim lim limiting distribution Lindeberg Condition linear combinations linear interpolation max in sup max sup monotone monotone function n+m+p nondecreasing obtained order statistics PAV algorithm points of increase proof replaced sample slogcom(O slope Stigler strictly increasing Substitution sufficiently large sums of order sup H Theorem III.l tion triangular array variance weak convergence condition weight function weighted midrange weighted sums Wiener process