2004

最新文章

• The golden chain - Discussion AI翻译
  作者：Freund, Y; Schapire, RE
  作者单位：Columbia University; Princeton University
• Saddlepoint approximation for moment generating functions of truncated random variables AI翻译
  作者：Butler, RW; Wood, ATA
  作者单位：Colorado State University System; Colorado State University Fort Collins; University of Nottingham
  摘要：We consider the problem of approximating the moment generating function (MGF) of a truncated random variable in terms of the MGF of the underlying (i.e., untruncated) random variable. The purpose of approximating the MGF is to enable the application of saddlepoint approximations to certain distributions determined by truncated random variables. Two important statistical applications are the following: the approximation of certain multivariate cumulative distribution functions; and the approxim...
• Wavelet-based estimation with multiple sampling rates AI翻译
  作者：Hall, P; Penev, S
  作者单位：Australian National University; University of London; London School Economics & Political Science; University of New South Wales Sydney
  摘要：We suggest an adaptive sampling rule for obtaining information from noisy signals using wavelet methods. The technique involves increasing the sampling rate when relatively high-frequency terms are incorporated into the wavelet estimator, and decreasing it when, again using thresholded terms as an empirical guide, signal complexity is judged to have decreased. Through sampling in this way the algorithm is able to accurately recover relatively complex signals without increasing the long-run ave...
• Least angle regression - Discussion AI翻译
  作者：Turlach, BA
  作者单位：University of Western Australia
• Approximately unbiased tests of regions using multistep-multiscale bootstrap resampling AI翻译
  作者：Shimodaira, H
  作者单位：Institute of Science Tokyo; Tokyo Institute of Technology
  摘要：Approximately unbiased tests based on bootstrap probabilities are considered for the exponential family of distributions with unknown expectation parameter vector, where the null hypothesis is represented as an arbitrary-shaped region with smooth boundaries. This problem has been discussed previously in Efron and Tibshirani [Ann. Statist. 26 (1998) 1687-1718], and a corrected p-value with second-order asymptotic accuracy is calculated by the two-level bootstrap of Efron, Halloran and Holmes [P...
• Estimators of diffusions with randomly spaced discrete observations: A general theory AI翻译
  作者：Aït-Sahalia, Y; Mykland, PA
  作者单位：Princeton University; National Bureau of Economic Research; University of Chicago
  摘要：We provide a general method to analyze the asymptotic properties of a variety of estimators of continuous time diffusion processes when the data are not only discretely sampled in time but the time separating successive observations may possibly be random. We introduce a new operator, the generalized infinitesimal generator, to obtain Taylor expansions of the asymptotic moments of the estimators. As a special case, our results apply to the situation where the data are discretely sampled at a f...
• On optimal spatial subsample size for variance estimation AI翻译
  作者：Nordman, DJ; Lahiri, SN
  作者单位：University of Wisconsin System; Iowa State University
  摘要：We consider the problem of determining the optimal block (or subsample) size for a spatial subsampling method for spatial processes observed on regular grids. We derive expansions for the mean square error of the subsampling variance estimator, which yields an expression for the theoretically optimal block size. The optimal block size is shown to depend in an intricate way on the geometry of the spatial sampling region as well as characteristics of the underlying random field. Final expression...
• Complexity regularization via localized random penalties AI翻译
  作者：Lugosi, G; Wegkamp, M
  作者单位：Pompeu Fabra University; State University System of Florida; Florida State University
  摘要：In this article, model selection via penalized empirical loss minimization in nonparametric classification problems is studied. Data-dependent penalties are constructed, which are based on estimates of the complexity of a small subclass of each model class, containing only those functions with small empirical loss. The penalties are novel since those considered in the literature are typically based on the entire model class. Oracle inequalities using these penalties are established, and the ad...
• Training samples in objective Bayesian model selection AI翻译
  作者：Berger, JO; Pericchi, LR
  作者单位：Duke University; University of Puerto Rico; University of Puerto Rico Rio Piedras
  摘要：Central to several objective approaches to Bayesian model selection is the use of training samples (subsets of the data), so as to allow utilization of improper objective priors. The most common prescription for choosing training samples is to choose them to be as small as possible, subject to yielding proper posteriors; these are called minimal training samples. When data can vary widely in terms of either information content or impact on the improper priors, use of minimal training samples c...
• Construction of E(s2)-optimal supersaturated designs AI翻译
  作者：Bulutoglu, DA; Cheng, CS
  作者单位：United States Department of Defense; United States Air Force; US Air Force Research Laboratory; Air Force Institute of Technology (AFIT); Academia Sinica - Taiwan
  摘要：Booth and Cox proposed the E(s(2)) criterion for constructing two-level supersaturated designs. Nguyen [Technometrics 38 (1996) 69-73] and Tang and Wu [Canad. J. Statist 25 (1997) 191-201] independently derived a lower bound for E(s(2)). This lower bound can be achieved only when m is a multiple of N - 1, where m is the number of factors and N is the run size. We present a method that uses difference families to construct designs that satisfy this lower bound. We also derive better lower bound...