6期

最新文章

• ON THE ESTIMATION OF INTEGRATED COVARIANCE MATRICES OF HIGH DIMENSIONAL DIFFUSION PROCESSES AI翻译
  作者：Zheng, Xinghua; Li, Yingying
  作者单位：Hong Kong University of Science & Technology
  摘要：We consider the estimation of integrated covariance (ICV) matrices of high dimensional diffusion processes based on high frequency observations. We start by studying the most commonly used estimator, the realized covariance (RCV) matrix. We show that in the high dimensional case when the dimension p and the observation frequency n grow in the same rate, the limiting spectral distribution (LSD) of RCV depends on the covolatility process not only through the targeting ICV, but also on how the co...
• SUFFICIENT DIMENSION REDUCTION BASED ON AN ENSEMBLE OF MINIMUM AVERAGE VARIANCE ESTIMATORS AI翻译
  作者：Yin, Xiangrong; Li, Bing
  作者单位：University System of Georgia; University of Georgia; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：We introduce a class of dimension reduction estimators based on an ensemble of the minimum average variance estimates of functions that characterize the central subspace, such as the characteristic functions, the Box-Cox transformations and wavelet basis. The ensemble estimators exhaustively estimate the central subspace without imposing restrictive conditions on the predictors, and have the same convergence rate as the minimum average variance estimates. They are flexible and easy to implemen...
• RATES OF CONTRACTION FOR POSTERIOR DISTRIBUTIONS IN Lr-METRICS, 1 ≤ r ≤ ∞ AI翻译
  作者：Gine, Evarist; Nickl, Richard
  作者单位：University of Connecticut; University of Cambridge
  摘要：The frequentist behavior of nonparametric Bayes estimates, more specifically, rates of contraction of the posterior distributions to shrinking L-r-norm neighborhoods, 1 <= r <= infinity, of the unknown parameter, are studied. A theorem for nonparametric density estimation is proved under general approximation-theoretic assumptions on the prior. The result is applied to a variety of common examples, including Gaussian process, wavelet series, normal mixture and histogram priors. The rates of co...
• MINIMAX ESTIMATION FOR MIXTURES OF WISHART DISTRIBUTIONS AI翻译
  作者：Haff, L. R.; Kim, P. T.; Koo, J. -Y.; Richards, D. St P.
  作者单位：University of California System; University of California San Diego; University of Guelph; Korea University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：The space of positive definite symmetric matrices has been studied extensively as a means of understanding dependence in multivariate data along with the accompanying problems in statistical inference. Many books and papers have been written on this subject, and more recently there has been considerable interest in high-dimensional random matrices with particular emphasis on the distribution of certain eigenvalues. With the availability of modern data acquisition capabilities, smoothing or non...
• HIGH-DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS AI翻译
  作者：Fan, Jianqing; Liao, Yuan; Mincheva, Martina
  作者单位：Princeton University
  摘要：The variance-covariance matrix plays a central role in the inferential theories of high-dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error cova...
• ON THE APPROXIMATE MAXIMUM LIKELIHOOD ESTIMATION FOR DIFFUSION PROCESSES AI翻译
  作者：Chang, Jinyuan; Chen, Song Xi
  作者单位：Peking University; Peking University; Iowa State University
  摘要：The transition density of a diffusion process does not admit an explicit expression in general, which prevents the full maximum likelihood estimation (MLE) based on discretely observed sample paths. Ait-Sahalia [J. Finance 54 (1999) 1361-1395; Econometrica 70 (2002) 223-262] proposed asymptotic expansions to the transition densities of diffusion processes, which lead to an approximate maximum likelihood estimation (AMLE) for parameters. Built on Ait-Sahalia's [Econometrica 70 (2002) 223-262; A...
• SADDLEPOINT APPROXIMATIONS FOR LIKELIHOOD RATIO LIKE STATISTICS WITH APPLICATIONS TO PERMUTATION TESTS AI翻译
  作者：Kolassa, John; Robinson, John
  作者单位：Rutgers University System; Rutgers University New Brunswick; University of Sydney
  摘要：We obtain two theorems extending the use of a saddlepoint approximation to multiparameter problems for likelihood ratio-like statistics which allow their use in permutation and rank tests and could be used in bootstrap approximations. In the first, we show that in some cases when no density exists, the integral of the formal saddlepoint density over the set corresponding to large values of the likelihood ratio-like statistic approximates the true probability with relative error of order 1/n. I...
• ACCURATE EMULATORS FOR LARGE-SCALE COMPUTER EXPERIMENTS AI翻译
  作者：Haaland, Ben; Qian, Peter Z. G.
  作者单位：National University of Singapore; National University of Singapore; University of Wisconsin System; University of Wisconsin Madison
  摘要：Large-scale computer experiments are becoming increasingly important in science. A multi-step procedure is introduced to statisticians for modeling such experiments, which builds an accurate interpolator in multiple steps. In practice, the procedure shows substantial improvements in overall accuracy, but its theoretical properties are not well established. We introduce the terms nominal and numeric error and decompose the overall error of an interpolator into nominal and numeric portions. Boun...
• PRINCIPAL SUPPORT VECTOR MACHINES FOR LINEAR AND NONLINEAR SUFFICIENT DIMENSION REDUCTION AI翻译
  作者：Li, Bing; Artemiou, Andreas; Li, Lexin
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Michigan Technological University; North Carolina State University
  摘要：We introduce a principal support vector machine (PSVM) approach that can be used for both linear and nonlinear sufficient dimension reduction. The basic idea is to divide the response variables into slices and use a modified form of support vector machine to find the optimal hyperplanes that separate them. These optimal hyperplanes are then aligned by the principal components of their normal vectors. It is proved that the aligned normal vectors provide an unbiased, root n-consistent, and asymp...
• ASYMPTOTIC PROPERTIES OF THE SEQUENTIAL EMPIRICAL ROC, PPV AND NPV CURVES UNDER CASE-CONTROL SAMPLING AI翻译
  作者：Koopmeiners, Joseph S.; Feng, Ziding
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; Fred Hutchinson Cancer Center
  摘要：The receiver operating characteristic (ROC) curve, the positive predictive value (PPV) curve and the negative predictive value (NPV) curve are three measures of performance for a continuous diagnostic biomarker. The ROC, PPV and NPV curves are often estimated empirically to avoid assumptions about the distributional form of the biomarkers. Recently, there has been a push to incorporate group sequential methods into the design of diagnostic biomarker studies. A thorough understanding of the asy...