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作者：MAMMEN, E
摘要：In this paper two bootstrap procedures are considered for the estimation of the distribution of linear contrasts and of F-test statistics in high dimensional linear models. An asymptotic approach will be chosen where the dimension p of the model may increase for sample size n --> infinity. The range of validity will be compared for the normal approximation and for the bootstrap procedures. Furthermore, it will be argued that the rates of convergence are different for the bootstrap procedures i...
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作者：MESSER, K; GOLDSTEIN, L
作者单位：University of Southern California
摘要：We introduce a new class of variable kernels which depend on the smoothing parameter b through a simple scaling operation, and which have good integrated mean square error (IMSE) convergence properties. These kernels deform ''automatically'' near the boundary, eliminating boundary bias. Computational formulas are given for all orders of kernel in terms of exponentially damped sines and cosines. The kernel is a computationally convenient approximation to a certain Green's function, with the res...
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作者：YING, ZL
摘要：Large sample approximations are developed to establish asymptotic linearity of the commonly used linear rank estimating functions, defined as stochastic integrals of counting processes over the whole line, for censored regression data. These approximations lead to asymptotic normality of the resulting rank estimators defined as solutions of the linear rank estimating equations. A second kind of approximations is also developed to show that the estimating functions can be uniformly approximated...
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作者：CHAI, FS; MAJUMDAR, D
作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
摘要：Yeh and Bradley conjectured that every binary connected block design with blocks of size k and a constant replication number r for each treatment can be converted to a linear trend-free design by permuting the positions of treatments within blocks if and only if r(k + 1) = 0 (mod 2). This conjecture is studied. Results include: (i) the conjecture is true whenever the block size is even and (ii) the conjecture is true for BIB designs.
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作者：PATIL, PN
摘要：It is known that the least squares cross-validation bandwidth is asymptotically optimal in the case of kernel-based density and hazard rate estimation in the settings of both complete and randomly right-censored samples. From a practical point of view, it is important to know at what rate the cross-validation bandwidth converges to the optimal. In this paper we answer this question in a general setup which unifies all four possible cases.
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作者：ROSENBERGER, WF
摘要：A response-adaptive treatment allocation design for a clinical trial attempts to place the majority of patients on the treatment that appears more successful, based on the responses of patients already treated. One example of such a design is the randomized play-the-winner rule developed by Wei and Durham, which randomizes the treatment assignment probabilities according to the outcomes of treatments previously assigned. For a trial with dichotomous treatment responses and a randomized play-th...
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作者：BARNDORFFNIELSEN, OE; BLAESILD, P
摘要：A variety of exponential models with affine dual foliations have been noted to possess certain rather similar statistical properties. To give a precise meaning to what has been conceived as ''similar'' we here propose a set of five conditions, of a differential geometric/statistical nature, that specify the class of what we term orthogeodesic models. It is discussed how these conditions capture the properties in question, and it is shown that some important nonexponential models turn out to sa...
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作者：LOW, MG
摘要：Renormalization arguments are used to derive optimal rates of convergence, under integrated squared error loss, for parameter spaces having a certain rectangular structure.
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作者：HARDLE, W; MAMMEN, E
作者单位：Humboldt University of Berlin
摘要：In general, there will be visible differences between a parametric and a nonparametric curve estimate. It is therefore quite natural to compare these in order to decide whether the parametric model could be justified. An asymptotic quantification is the distribution of the integrated squared difference between these curves. We show that the standard way of boot-strapping this statistic fails. We use and analyse a different form of bootstrapping for this task. We call this method the wild boots...
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作者：HSING, T
摘要：Under stationarity and weak dependence, the statistical significance and the estimation of the extremal index are considered. It is shown that the distribution of the sample maximum can be uniformly approximated given the extremal index and the marginal distribution as the sample size increases. An adaptive procedure is proposed for estimating the extremal index. The procedure is shown to be asymptotically optimal in a class of estimators.
