-
作者：Cheng, CS; Mukerjee, R
作者单位：University of California System; University of California Berkeley; Indian Institute of Management (IIM System); Indian Institute of Management Calcutta
摘要：Using the approach of finite projective geometry, we make a systematic study of estimation capacity, a criterion of model robustness, under the absence of interactions involving three or more factors. Some general results, providing designs with maximum estimation capacity, are obtained. In particular, for two-level factorials, it is seen that constructing a design with maximum estimation capacity calls for choosing points from a finite projective geometry such that the number of lines is maxi...
-
作者：Ishwaran, H
作者单位：Cleveland Clinic Foundation
摘要：Advances in Markov chain Monte Carlo (MCMC) methods now make it computationally feasible and relatively straightforward to apply the Dirichlet process prior in a wide range of Bayesian nonparametric problems. The feasibility of these methods rests heavily on the fact that the MCMC approach avoids direct sampling of the Dirichlet process and is instead based on sampling the finite-dimensional posterior which is obtained from marginalizing out the process. In application, it is the integrated po...
-
作者：Müller-Gronbach, T; Ritter, K
作者单位：Free University of Berlin; University of Passau
摘要：We study integration and reconstruction of Gaussian random functions with inhomogeneous local smoothness. A single realization may only be observed at a finite sampling design and the correct local smoothness is unknown. We construct adaptive two-stage designs that lead to asymptotically optimal methods. We show that every nonadaptive design is less efficient.
-
作者：Poor, HV
作者单位：Princeton University
摘要：The problem of detecting a change in the probability distribution of a random sequence is considered. Stopping times are derived that optimize the tradeoff between detection delay and false alarms within two criteria. In both cases, the detection delay is penalized exponentially rather than Linearly, as has been the case in previous formulations of this problem. The first of these two criteria is to minimize a worst-case measure of the exponential detection delay within a lower-bound constrain...
-
作者：Greenwood, PE; McKeague, IW; Wefelmeyer, W
作者单位：University of British Columbia; State University System of Florida; Florida State University; State University System of Florida; Florida State University; Universitat Siegen
摘要：If we wish to estimate efficiently the expectation of an arbitrary function on the basis of the output of a Gibbs sampler, which is better: deterministic or random sweep? In each case we calculate the asymptotic variance of the empirical estimator, the average of the function over the output, and determine the minimal asymptotic variance for estimators that use no information about the underlying distribution. The empirical estimator has noticeably smaller variance for deterministic sweep. The...
-
作者：van Es, B; Jongbloed, G; van Zuijlen, M
作者单位：University of Amsterdam; Vrije Universiteit Amsterdam; Radboud University Nijmegen
摘要：A new nonparametric estimation procedure is introduced for the distribution function in a class of deconvolution problems, where the convolution density has one discontinuity. The estimator is shown to be consistent and its cube root asymptotic distribution theory is established. Known results on the minimax risk for the estimation problem indicate the estimator to be efficient.
-
作者：Hartigan, JA
作者单位：Yale University
摘要：Consider an estimate theta* of a parameter theta based on repeated observations from a family of densities f(theta) evaluated by the Kullback-Leibler loss function K(theta, theta*) = integral log(f(theta)/f(theta*))f(theta). The maximum likelihood prior density, if it exists, is the density for which the corresponding Bayes estimate is asymptotically negligibly different from the maximum likelihood estimate. The Bayes estimate corresponding to the maximum likelihood prior is identical to maxim...
-
作者：Choudhuri, N
作者单位：University of Michigan System; University of Michigan
摘要：This paper shows that the Bayesian bootstrap (BB) distribution of a multidimensional mean functional based on i.i.d. observations has a strongly unimodal Lebesgue density provided the convex hull of the data has a nonempty interior. This result is then used to construct the finite sample BE credible sets. The influence of an outlier on these credible sets is studied in detail and a comparison is made with the empirical likelihood ratio confidence sets in this context.
-
作者：Cohen, A; Sackrowitz, HB
作者单位：Rutgers University System; Rutgers University New Brunswick
摘要：Consider one-sided testing problems for a multivariate exponential family model. Through conditioning or other considerations, the problem oftentimes reduces to testing a null hypothesis that the natural parameter is a zero vector against the alternative that the natural parameter lies in a closed convex cone l. The problems include testing homogeneity of parameters, testing independence in contingency tables, testing stochastic ordering of distributions and many others. A test methodology is ...
-
作者：Golubev, GK; Levit, BY
作者单位：Russian Academy of Sciences; Utrecht University
摘要：We consider the classical Wicksell problem of estimating an unknown distribution function G of the radii of balls, based on their observed cross-sections. It is assumed that the underlying distribution function G belongs to a Holder class of smoothness gamma > 1/2. We prove that, for a suitable choice of the smoothing parameters, kernel-type estimators are asymptotically efficient for a large class of symmetric bowl-shaped loss functions.
