2004

最新文章

• Local global neural networks:: A new approach for nonlinear time series modeling AI翻译
  作者：Suárez-Fariñas, M; Pedreira, CE; Medeiros, MC
  作者单位：Pontificia Universidade Catolica do Rio de Janeiro; Pontificia Universidade Catolica do Rio de Janeiro
  摘要：We propose the local-global neural networks model within the context of time series models. This formulation encompasses some already existing nonlinear models and also admits the mixture of experts approach. We emphasize the linear expert case and extensively discuss the theoretical aspects of the model: stationarity conditions, existence, consistency and asymptotic normality of the parameter estimates, and model identifiability. The proposed model consists of a mixture of stationary and nons...
• Calibrated probabilistic mesoscale weather field forecasting: The geostatistical output perturbation method - Comment AI翻译
  作者：Tebaldi, C; Nychka, D
  作者单位：National Center Atmospheric Research (NCAR) - USA
• Location-scale depth - Comment AI翻译
  作者：He, XM; Portnoy, S
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign
• Smooth design-adapted wavelets for nonparametric stochastic regression AI翻译
  作者：Delouille, V; Simoens, J; von Sachs, R
  作者单位：Rice University; Universite Catholique Louvain; Universite Catholique Louvain
  摘要：We treat nonparametric stochastic regression using smooth design-adapted wavelets built by means of the lifting scheme. The proposed method automatically adapts to the nature of the regression problem, that is, to the irregularity of the design, to data on the interval, and to arbitrary sample sizes (which do not need to be a power of 2). As such, this method provides a uniform solution to the usual criticisms of first-generation wavelet estimators. More precisely, starting from the unbalanced...
• Hierarchical Bayesian neural networks: An application to a prostate cancer study AI翻译
  作者：Ghosh, M; Maiti, T; Kim, D; Chakraborty, S; Tewari, A
  作者单位：State University System of Florida; University of Florida; Iowa State University; Kyungpook National University (KNU); Henry Ford Health System; Henry Ford Hospital; Henry Ford Health System; Henry Ford Hospital; Henry Ford Health System; Henry Ford Hospital
  摘要：Prostate cancer is one of the most common cancers in American men. Management depends on the staging of prostate cancer. Only cancers that are confined to organs of origin are potentially curable. The article considers a hierarchical Bayesian neural network approach for posterior prediction probabilities of certain features indicative of non-organ-confined prostate cancer. The Bayesian procedure is implemented by an application of the Markov chain Monte Carlo numerical integration technique. F...
• A Bayesian insertion/deletion algorithm for distant protein motif searching via entropy filtering AI翻译
  作者：Xie, J; Li, KC; Bina, M
  作者单位：Purdue University System; Purdue University; University of California System; University of California Los Angeles; Purdue University System; Purdue University
  摘要：Bayesian models have been developed that find ungapped motifs in multiple protein sequences. In (his article. we extend the model to allow for deletions and insertions in motifs. Direct generalization of the ungapped algorithm, based on Gibbs sampling, proved unsuccessful because the configuration space became much larger. To alleviate the convergence difficulty, a two-stage procedure is introduced. At the first stage. we develop a method called entropy filtering, which quick]), searchs good s...
• Full matching in an observational study of coaching for the SAT AI翻译
  作者：Hansen, BB
  作者单位：University of Michigan System; University of Michigan
  摘要：Among matching techniques for observational studies, full matching is in principle the best, in the sense that its alignment of comparable treated and control subjects is as good as that of any alternate method, and potentially much better. This article evaluates the practical performance of full matching for the first time, modifying it in order to minimize variance as well as bias and then using it to compare coached and uncoached takers of the SAT. In this new version, with restrictions on ...
• A semiparametric basis for combining estimation problems under quadratic loss AI翻译
  作者：Judge, GG; Mittelhammer, RC
  作者单位：University of California System; University of California Berkeley; Washington State University
  摘要：When there is uncertainty concerning the appropriate statistical model-estimator to use in representing the data sampling process, we consider a basis for optimally combining estimation problems. The objective is to produce natural adaptive estimators that are free of subjective choices and tuning parameters. In the context of two competing multivariate linear statistical models-estimators, we demonstrate a semiparametric Stein-like (SPSL) estimator, (beta) over bar((alpha) over cap), that, un...
• Fully exponential Laplace approximations using asymptotic modes AI翻译
  作者：Miyata, Y
  作者单位：Waseda University
  摘要：Posterior means of positive functions can be expressed as the ration integrals which is called fully exponential form. When approximating the posterior means analytically, we usually use Laplace's method. Tierney and Kadane presented a second-order approximation by using the Laplace approximations in each of the numerator and denominator of the fully exponential form. However, Laplace's method requires the exact mode of the integrand. In this article we introduce the concept of asymptotic mode...
• Methods and criteria for model selection AI翻译
  作者：Kadane, JB; Lazar, NA
  作者单位：Carnegie Mellon University
  摘要：Model selection is an important part of any statistical analysis and, indeed, is central to the pursuit of science in general. Many authors have examined the question of model selection from both frequentist and Bayesian perspectives, and many tools for selecting the best model have been suggested in the literature. This paper considers the various proposals from a Bayesian decision-theoretic perspective.