6期

最新文章

• Improved nonnegative estimation of multivariate components of variance AI翻译
  作者：Srivastava, MS; Kubokawa, T
  作者单位：University of Toronto; University of Tokyo
  摘要：In this paper, we consider a multivariate one-way random effect model with equal replications. We propose nonnegative definite estimators for between and within components of variance. Under the Stein loss function, it is shown that the proposed estimators of the within component dominate the best unbiased estimator. Restricted maximum likelihood, truncated and order-preserving minimax estimators are also proposed. A Monte Carlo simulation is carried out to choose among these estimators. For e...
• Adaptive model selection using empirical complexities AI翻译
  作者：Lugosi, G; Nobel, AB
  作者单位：Pompeu Fabra University; University of North Carolina; University of North Carolina Chapel Hill
  摘要：Given n independent replicates of a jointly distributed pair (X, Y) epsilon R(d) x R x , we wish to select from a fixed sequence of model classes F(1), F(2),... a deterministic prediction rule f: R(d) --> R whose risk is small. WE investigate the possibility of empirically assessing the complexity of each model class, that is, the actual difficulty of the estimation problem within each class. The estimated complexities are in turn used to define an adaptive model selection procedure, which is ...
• Smooth discrimination analysis AI翻译
  作者：Mammen, E; Tsybakov, AB
  作者单位：Ruprecht Karls University Heidelberg; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Sorbonne Universite; Universite Paris Cite
  摘要：Discriminant analysis for two data sets in R-d with probability densities f and g can be based on the estimation of the set G = {x:f(x) greater than or equal to g(x)}. We consider applications where it is appropriate to assume that the region G has a smooth boundary or belongs to another nonparametric class of sets. In particular, this assumption makes sense if discrimination is used as a data analytic tool. Decision rules based on minimization of empirical risk over the whole class of sets an...
• Adaptive wavelet estimator for nonparametric density deconvolution AI翻译
  作者：Pensky, M; Vidakovic, B
  作者单位：State University System of Florida; University of Central Florida; Duke University
  摘要：The problem of estimating a density g based on a sample X-1, X-2, X-n from p = q * g is considered. Linear and nonlinear wavelet estimators teased on Meyer-type wavelets are constructed. The estimators are asymptotically optimal and adaptive if g belongs to the Sobolev space H-alpha. Moreover, the estimators considered in this paper adjust automatically to the situation when g is supersmooth.
• Theory of optimal blocking of 2n-m designs AI翻译
  作者：Chen, HG; Cheng, CS
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of California System; University of California Berkeley
  摘要：In this paper, we define the blocking wordlength pattern of a blocked fractional factorial design by combining the wordlength patterns of treatment-defining words and block-defining words. The concept of minimum aberration can be defined in terms of the blocking wordlength pattern and provides a good measure of the estimation capacity of a blocked fractional factorial design. By blending techniques of coding theory and finite projective geometry, we obtain combinatorial identities that govern ...
• Conditional inference about generalized linear mixed models AI翻译
  作者：Jiang, JM
  作者单位：University System of Ohio; Case Western Reserve University
  摘要：We propose a method of inference for generalized linear mixed models (GLMM) that in many ways resembles the method of least squares. We also show that adequate inference about GLMM can be made based on the conditional likelihood on a subset of the random effects. One of the important features of our methods is that they rely on weak distributional assumptions about the random effects. The methods proposed are also computationally feasible. Asymptotic behavior of the estimates is investigated. ...
• On prediction of individual sequences AI翻译
  作者：Cesa-Bianchi, N; Lugosi, G
  作者单位：University of Milan; Pompeu Fabra University
  摘要：Sequential randomized prediction of an arbitrary binary sequence is investigated. No assumption is made on the mechanism of generating the bit sequence. The goal of the predictor is to minimize its relative loss (or regret), that; is, to make almost as few mistakes as the best expert in a fixed, possibly infinite, set of experts. We point out a surprising connection between this prediction problem and empirical process theory. First, in the special case of static (memoryless) expert, we comple...
• Local asymptotic normality for regression models with long-memory disturbance AI翻译
  作者：Hallin, M; Taniguchi, M; Serroukh, A; Choy, K
  作者单位：Universite Libre de Bruxelles; Universite Libre de Bruxelles; University of Osaka; Imperial College London; Komazawa University
  摘要：The local asymptotic normality property is established fur a regression model with fractional ARIMA(p, d, q) errors. This result allows for solving, in an asymptotically optimal way, a variety of inference problems In the long-memory context: hypothesis testing, discriminant analysis, rank-based testing, locally asymptotically minimax and adaptive estimation, etc. The problem of testing linear constraints on the parameters, the discriminant analysis problem, and the construction of locally asy...
• Large sample Bayesian analysis for geo/G/1 discrete-time queueing models AI翻译
  作者：Conti, PL
  作者单位：University of Bologna; Duke University
  摘要：In this paper, a nonparametric Bayesian analysis of queueing models with geometric input and general service time is performed. In particular, statistical inference for the probability generating function (p.g.f.) of the equilibrium waiting time distribution is considered. The consistency of the posterior distribution for such a p.g.f., as well as the weak convergence to a Gaussian process of a suitable rescaling, are proved. As by-products, results on statistical inference for queueing charac...
• Minimum G2-aberration for nonregular fractional factorial designs AI翻译
  作者：Tang, BX; Deng, LY
  作者单位：University of Memphis
  摘要：Deng and Tang proposed generalized resolution and minimum aberration criteria for comparing and assessing nonregular fractional factorials, of which Plackett-Burman designs are special cases. A relaxed variant of generalized aberration is proposed and studied in this paper. We show that a best design according to this criterion minimizes the contamination of nonnegligible interactions on the estimation of main effects in the order of importance given by the hierarchical assumption. The new cri...