3期

最新文章

• Oracle inequalities for inverse problems AI翻译
  作者：Cavalier, L; Golubev, GK; Picard, D; Tsybakov, AB
  作者单位：Aix-Marseille Universite; Sorbonne Universite; Universite Paris Cite; Sorbonne Universite; Universite Paris Cite
  摘要：We consider a sequence space model of statistical linear inverse problems where we need to estimate a function f from indirect noisy observations. Let a finite set A of linear estimators be given. Our aim is to mimic the estimator in A that has the smallest risk on the true f. Under general conditions, we show that this can be achieved by simple minimization of an unbiased risk estimator, provided the singular values of the operator of the inverse problem decrease as a power law. The main resu...
• Empirical likelihood-based inference under imputation for missing response data AI翻译
  作者：Wang, QH; Rao, JNK
  作者单位：Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Peking University; Carleton University
  摘要：Inference under kernel regression imputation for missing response data is considered. An adjusted empirical likelihood approach to inference for the mean of the response variable is developed. A nonparametric version of Wilks' theorem is proved for the adjusted empirical log-likelihood ratio by showing that it has an asymptotic standard chi-squared distribution, and the corresponding empirical likelihood confidence interval for the mean is constructed. With auxiliary information, an empirical ...
• The publications and writings of Lucien Le Cam AI翻译
  作者：[Anonymous]
• Deficiency distance between multinomial and multivariate normal experiments AI翻译
  作者：Carter, AV
  作者单位：University of California System; University of California Santa Barbara
  摘要：The deficiency distance between a multinomial and a multivariate normal experiment is bounded under a condition that the parameters are bounded away from zero. This result can be used as a key step in establishing asymptotic normal approximations to nonparametric density estimation experiments. The bound relies on the recursive construction of explicit Markov kernels that can be used to reproduce one experiment from the other. The distance is then bounded using classic local-limit bounds betwe...
• Recovering edges in ill-posed inverse problems:: Optimality of curvelet frames AI翻译
  作者：Candès, EJ; Donoho, DL
  作者单位：Stanford University
  摘要：We consider a model problem of recovering a function f (x(1), x(2)) from noisy Radon data. The function f to be recovered is assumed smooth apart from a discontinuity along a C-2 curve, that is, an edge. We use the continuum white-noise model, with noise level epsilon. Traditional linear methods for solving such inverse problems behave poorly in the presence of edges. Qualitatively, the reconstructions are blurred near the edges; quantitatively, they give in our model mean squared errors (MSEs...
• Effect of extrapolation on coverage accuracy of prediction intervals computed from Pareto-type data AI翻译
  作者：Hall, P; Peng, L; Tajvidi, N
  作者单位：Australian National University; Lund University
  摘要：A feature that distinguishes extreme-value contexts from more conventional statistical problems is that in the former we often wish to make predictions well beyond the range of the data. For example, one might have a 10-year sequence of observations of a phenomenon, and wish to make forecasts for the next 20 to 30 years. It is generally unclear how such long ranges of extrapolation affect prediction. In the present paper, and for extremes from a distribution with regularly varying tails at inf...
• Blocked regular fractional factorial designs with maximum estimation capacity (vol 29, pg 530, 2001) AI翻译
  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
• Asymptotic nonequivalence of GARCH models and diffusions AI翻译
  作者：Wang, YZ
  作者单位：University of Connecticut
  摘要：This paper investigates the statistical relationship of the LARCH model and its diffusion limit. Regarding the two types of models as two statistical experiments formed by discrete observations from the models, we study their asymptotic equivalence in terms of Le Cam's deficiency distance. To our surprise, we are able to show that the LARCH model and its diffusion limit are asymptotically equivalent only under deterministic volatility. With stochastic volatility, due to the difference between ...
• The statistical work of Lucien Le Cam AI翻译
  作者：van der Vaart, A
  作者单位：Vrije Universiteit Amsterdam
  摘要：We give an overview and appraisal of the scientific work in theoretical statistics, and its impact, by Lucien Le Cam. The references to Le Cam's papers refer to the Le Cam bibliography. The reference is the first paper for the given year if not stated.
• Asymptotic equivalence theory for nonparametric regression with random design AI翻译
  作者：Brown, LD; Cai, TT; Low, MG; Zhang, CH
  作者单位：University of Pennsylvania; Rutgers University System; Rutgers University New Brunswick
  摘要：This paper establishes the global asymptotic equivalence between the nonparametric regression with random design and the white noise under sharp smoothness conditions on an unknown regression or drift function. The asymptotic equivalence is established by constructing explicit equivalence mappings between the nonparametric regression and the white-noise experiments, which provide synthetic observations and synthetic asymptotic solutions from any one of the two experiments with asymptotic prope...