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• Endogenous post-stratification in surveys: Classifying with a sample-fitted model AI翻译
  作者：Breidt, F. Jay; Opsomer, Jean D.
  作者单位：Colorado State University System; Colorado State University Fort Collins
  摘要：Post-stratification is frequently used to improve the precision of survey estimators when categorical auxiliary information is available from sources outside the survey. In natural resource surveys, such information is often obtained from remote sensing data, classified into categories and displayed as pixel-based maps. These maps may be constructed based on classification models fitted to the sample data. Post-stratification of the sample data based on categories derived from the sample data ...
• High breakdown point robust regression with censored data AI翻译
  作者：Salibian-Barrera, Matias; Yohai, Victor J.
  作者单位：University of British Columbia; University of Buenos Aires
  摘要：In this paper, we propose a class of high breakdown point estimators for the linear regression model when the response variable contains censored observations. These estimators are robust against high-leverage outliers and they generalize the LMS (least median of squares), S, MM and tau-estimators for linear regression. An important contribution of this paper is that we can define consistent estimators using a bounded loss function (or equivalently, a re-descending score function). Since the c...
• Approximation and learning by greedy algorithms AI翻译
  作者：Barron, Andrew R.; Cohen, Albert; Dahmen, Wolfgang; DeVore, Ronald A.
  作者单位：Yale University; Sorbonne Universite; Universite Paris Cite; RWTH Aachen University; University of South Carolina System; University of South Carolina Columbia
  摘要：We consider the problem of approximating a given element f from a Hilbert space H by means of greedy algorithms and the application of such procedures to the regression problem in statistical learning theory. We improve on the existing theory of convergence rates for both the orthogonal greedy algorithm and the relaxed greedy algorithm, as well as for the forward stepwise projection algorithm. For all these algorithms, we prove convergence results for a variety of function classes and not simp...
• Asymptotic inference in some heteroscedastic regression models with long memory design and errors AI翻译
  作者：Guo, Hongwen; Koul, Hira L.
  作者单位：Michigan State University
  摘要：This paper discusses asymptotic distributions of various estimators of the underlying parameters in some regression models with long memory (LM) Gaussian design and nonparametric heteroscedastic LM moving average errors. In the simple linear regression model, the first-order asymptotic distribution of the least square estimator of the slope parameter is observed to be degenerate. However, in the second order, this estimator is n(1/2)-consistent and asymptotically normal for h + H < 3/2; nonnor...
• Properties of higher criticism under strong dependence AI翻译
  作者：Hall, Peter; Jin, Jiashun
  作者单位：University of Melbourne; University of California System; University of California Davis; Purdue University System; Purdue University
  摘要：The problem of signal detection using sparse, faint information is closely related to a variety of contemporary statistical problems, including the control of false-discovery rate, and classification using very high-dimensional data. Each problem can be solved by conducting a large number of simultaneous hypothesis tests, the properties of which are readily accessed under the assumption of independence. In this paper we address the case of dependent data, in the context of higher criticism met...
• Stability of the Gibbs sampler for Bayesian hierarchical models AI翻译
  作者：Papaspiliopoulos, Omiros; Roberts, Gareth
  作者单位：University of Warwick
  摘要：We characterize the convergence of the Gibbs sampler which samples from the joint posterior distribution of parameters and missing data in hierarchical linear models with arbitrary symmetric error distributions. We show that the convergence can be uniform, geometric or subgeometric depending on the relative tail behavior of the error distributions, and on the parametrization chosen. Our theory is applied to characterize the convergence of the Gibbs sampler on latent Gaussian process models. We...
• A test for model specification of diffusion processes AI翻译
  作者：Chen, Song Xi; Gao, Jiti; Tang, Cheng Yong
  作者单位：Iowa State University; University of Western Australia
  摘要：We propose a test for model specification of a parametric diffusion process based on a kernel estimation of the transitional density of the process. The empirical likelihood is used to formulate a statistic, for each kernel smoothing bandwidth, which is effectively a Studentized L-2-distance between the kernel transitional density estimator and the parametric transitional density implied by the parametric process. To reduce the sensitivity of the test on smoothing bandwidth choice, the final t...
• Random fields of multivariate test statistics, with applications to shape analysis AI翻译
  作者：Taylor, J. E.; Worsley, K. J.
  作者单位：Stanford University; Universite de Montreal; McGill University
  摘要：Our data are random fields of multivariate Gaussian observations, and we fit a multivariate linear model with common design matrix at each point. We are interested in detecting those points where some of the coefficients are nonzero using classical multivariate statistics evaluated at each point. The problem is to find the P-value of the maximum of such a random field of test statistics. We approximate this by the expected Euler characteristic of the excursion set. Our main result is a very si...
• Locally D-optimal designs based on a class of composed models resulted from blending Emax and one-compartment models AI翻译
  作者：Fang, X.; Hedayat, A. S.
  作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
  摘要：A class of nonlinear models combining a pharmacokinetic compartmental model and a pharmacodynamic Emax model is introduced. The locally D-optimal (LD) design for a four-parameter composed model is found to be a saturated four-point uniform LD design with the two boundary points of the design space in the LD design support. For a five-parameter composed model, a sufficient condition for the LD design to require the minimum number of sampling time points is derived. Robust LD designs are also in...
• Nonlinear estimation for linear inverse problems with error in the operator AI翻译
  作者：Hoffmann, Marc; Reiss, Markus
  作者单位：Universite Paris-Est-Creteil-Val-de-Marne (UPEC); Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Universite Gustave-Eiffel; Ruprecht Karls University Heidelberg
  摘要：We study two nonlinear methods for statistical linear inverse problems when the operator is not known. The two constructions combine Galerkin regularization and wavelet thresholding. Their performances depend on the underlying structure of the operator, quantified by an index of sparsity. We prove their rate-optimality and adaptivity properties over Besov classes.