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作者：WOODRUFF, DL; ROCKE, DM
摘要：Estimation of multivariate shape and location in a fashion that is robust with respect to outliers and is affine equivariant represents a significant challenge. The use of compound estimators that use a combinatorial estimator such as Rousseeuw's minimum volume ellipsoid (MVE) or minimum covariance determinant (MCD) to find good starting points for high-efficiency robust estimators such as S estimators has been proposed. In this article we indicate why this scheme will fail in high dimension d...
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作者：HUGHESOLIVER, JM; SWALLOW, WH
摘要：A method for adaptively estimating a proportion p using group-testing procedures is presented and analyzed, with emphasis placed on a two-stage procedure. This estimator is compared to the usual group-testing estimator via asymptotic and small-sample relative efficiency. The adaptive estimator is generally recommended with the restriction that adaptations (i.e., adjustments of group size) are based on at least 10 measurements/responses. But if one is confident that one has a ''very good'' a pr...
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作者：CHEN, MH
摘要：Markov chain sampling schemes generate dependent observations {Theta(i), 0 less than or equal to i less than or equal to n} from a full joint posterior distribution pi(theta\data). Frequently, only certain marginals of this full posterior density are of interest; thus an interesting problem is how to estimate the marginal posterior densities based on the dependent observations {Theta(i), 0 less than or equal to i less than or equal to n} from pi(theta\data). We propose a new importance-weighte...
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作者：TOMAN, B
摘要：Two- and three-level factorial designs are often used for exploratory experiments with many independent variables. The purpose of such experiments is to estimate the effects of all active independent variables and their interactions. For reasons of economy or other constraints, only a fraction of the full number of experimental settings of the independent variables may be run, precluding the separate data-based estimation of all the effects. In this situation of relatively sparse data and many...
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作者：LU, HHS; WELLS, MT; TIWARI, RC
作者单位：Cornell University; University of North Carolina; University of North Carolina Charlotte
摘要：For two distribution functions, F and G, the shift function is defined by Delta(t) = G(-1) . F(t) - t. The shift function is the distance from the 45 degrees line and the quantity plotted in Q-Q plots. In the analysis of lifetime data, Delta represents the difference between two treatments. The shift function can also be used to find crossing points of two distribution functions. The large-sample distribution theory for estimates of Delta is studied for right-censored data. It turns out that t...
