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作者：WIJSMAN, RA
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作者：BREIMAN, L; TSUR, Y; ZEMEL, A
作者单位：University of Minnesota System; University of Minnesota Twin Cities; Ben-Gurion University of the Negev
摘要：A simple and tractable iterative least squares estimation procedure for censored regression models with known error distributions is analyzed. It is found to be equivalent to a well-defined Huber type M-estimate. Under a regularity condition, the algorithm converges geometrically to a unique solution. The resulting estimate is square-root N-consistent and asymptotically normal.
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作者：NEUHAUS, G
摘要：For the two-sample problem with randomly censored data, there exists a general asymptotic theory of rank statistics which are functionals of stochastic integrals with respect to certain empirical martingales. In the present paper a conditional counterpart of this theory is developed. The conditional martingales are versions of the original ones reduced to the unit interval having their jumps at fixed lattice points. The resulting conditional tests are strictly distribution free under the null ...
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作者：SIEGMUND, D; ZHANG, HP
作者单位：Yale University
摘要：Using an expression for the expected number of local maxima of a random field, we derive an upper bound for the volume of a tube about a manifold in the unit sphere and show that under certain conditions our bound agrees with the evaluation of the tube volume in Weyl's formula. Applications to tests and confidence regions in nonlinear regression are discussed.
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作者：DAVIES, PL
摘要：Section 1 of the paper contains a general discussion of robustness. In Section 2 the influence function of the Hampel-Rousseeuw least median of squares estimator is derived. Linearly invariant weak metrics are constructed in Section 3. It is shown in Section 4 that S-estimators satisfy an exact Holder condition of order 1/2 at models with normal errors. In Section 5 the breakdown points of the Hampel-Krasker dispersion and regression functionals are shown to be 0. The exact breakdown point of ...
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作者：GASSIAT, E
摘要：We consider the estimation problem of the parameter b of a stationary AR(p) process without any of the usual causality assumptions. The aim of the paper is to derive asymptotic minimax bounds for estimators of b. When the distribution of the noise is known, we show LAN properties of the model and derive locally asymptotically minimax (LAM) estimators. The most important results are about the case of unknown distribution: The main result shows that, if one uses the usual parametrization, these ...
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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：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...
