2012

最新文章

• The phylogenetic Kantorovich-Rubinstein metric for environmental sequence samples AI翻译
  作者：Evans, Steven N.; Matsen, Frederick A.
  作者单位：Fred Hutchinson Cancer Center; University of California System; University of California Berkeley
  摘要：. It is now common to survey microbial communities by sequencing nucleic acid material extracted in bulk from a given environment. Comparative methods are needed that indicate the extent to which two communities differ given data sets of this type. UniFrac, which gives a somewhat ad hoc phylogenetics-based distance between two communities, is one of the most commonly used tools for these analyses. We provide a foundation for such methods by establishing that, if we equate a metagenomic sample ...
• Conditional quantile analysis when covariates are functions, with application to growth data AI翻译
  作者：Chen, Kehui; Mueller, Hans-Georg
  作者单位：University of California System; University of California Davis
  摘要：. Motivated by the conditional growth charts problem, we develop a method for conditional quantile analysis when predictors take values in a functional space. The method proposed aims at estimating conditional distribution functions under a generalized functional regression framework. This approach facilitates balancing of model flexibility and the curse of dimensionality for the infinite dimensional functional predictors. Its good performance in comparison with other methods, both for sparsel...
• Control Variates for Estimation Based on Reversible Markov Chain Monte Carlo Samplers AI翻译
  作者：Dellaportas, Petros; Kontoyiannis, Ioannis
  作者单位：Athens University of Economics & Business; Athens University of Economics & Business
  摘要：A general methodology is introduced for the construction and effective application of control variates to estimation problems involving data from reversible Markov chain Monte Carlo samplers. We propose the use of a specific class of functions as control variates, and we introduce a new consistent estimator for the values of the coefficients of the optimal linear combination of these functions. For a specific Markov chain Monte Carlo scenario, the form and proposed construction of the control ...
• Joint composite estimating functions in spatiotemporal models AI翻译
  作者：Bai, Yun; Song, Peter X. -K.; Raghunathan, T. E.
  作者单位：University of Michigan System; University of Michigan
  摘要：. Modelling of spatiotemporal processes has received considerable attention in recent statistical research. However, owing to the high dimensionality of the data, the joint modelling of spatial and temporal processes presents a great computational challenge, in both likelihood-based and Bayesian approaches. We propose a joint composite estimating function approach to estimating spatiotemporal covariance structures. This substantially reduces the computational complexity and is more efficient t...
• Reduced rank stochastic regression with a sparse singular value decomposition AI翻译
  作者：Chen, Kun; Chan, Kung-Sik; Stenseth, Nils Chr.
  作者单位：University of Iowa; Kansas State University; University of Oslo
  摘要：. For a reduced rank multivariate stochastic regression model of rank r*, the regression coefficient matrix can be expressed as a sum of r* unit rank matrices each of which is proportional to the outer product of the left and right singular vectors. For improving predictive accuracy and facilitating interpretation, it is often desirable that these left and right singular vectors be sparse or enjoy some smoothness property. We propose a regularized reduced rank regression approach for solving t...
• Adaptive and Dynamic Adaptive Procedures for False Discovery Rate Control and Estimation AI翻译
  作者：Casella, G.; Roberts, G.
  摘要：Many methods for estimation or control of the false discovery rate (FDR) can be improved by incorporating information about pi(0), the proportion of all tested null hypotheses that are true. Estimates of pi(0) are often based on the number of p-values that exceed a threshold lambda. We first give a finite sample proof for conservative point estimation of the FDR when the lambda-parameter is fixed. Then we establish a condition under which a dynamic adaptive procedure, whose lambda-parameter is...
• The relative frailty variance and shared frailty models AI翻译
  作者：Farrington, C. Paddy; Unkel, Steffen; Anaya-Izquierdo, Karim
  作者单位：Open University - UK; University of London; London School of Hygiene & Tropical Medicine; Open University - UK
  摘要：The relative frailty variance among survivors provides a readily interpretable measure of how the heterogeneity of a population, as represented by a frailty model, evolves over time. We discuss the properties of the relative frailty variance, show that it characterizes frailty distributions and that, suitably rescaled, it may be used to compare patterns of dependence across models and data sets. In shared frailty models, the relative frailty variance is closely related to the cross-ratio funct...
• Probabilistic Index Models AI翻译
  作者：Thas, Olivier; Neve, Jan De; Clement, Lieven; Ottoy, Jean-Pierre
  作者单位：Ghent University; University of Wollongong; Ghent University
  摘要：We present a semiparametric statistical model for the probabilistic index which can be defined as P(Y <= Y*), where Y and Y* are independent random response variables associated with covariate patterns X and X* respectively. A link function defines the relationship between the probabilistic index and a linear predictor. Asymptotic normality of the estimators and consistency of the covariance matrix estimator are established through semiparametric theory. The model is illustrated with several e...
• Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation AI翻译
  作者：Fearnhead, Paul; Prangle, Dennis
  作者单位：Lancaster University
  摘要：. Many modern statistical applications involve inference for complex stochastic models, where it is easy to simulate from the models, but impossible to calculate likelihoods. Approximate Bayesian computation (ABC) is a method of inference for such models. It replaces calculation of the likelihood by a step which involves simulating artificial data for different parameter values, and comparing summary statistics of the simulated data with summary statistics of the observed data. Here we show ho...
• The dynamic expectation-conditional maximization either' algorithm AI翻译
  作者：He, Yunxiao; Liu, Chuanhai
  作者单位：Purdue University System; Purdue University; Yale University
  摘要：. The expectationconditional maximization either (ECME) algorithm has proven to be an effective way of accelerating the expectationmaximization algorithm for many problems. Recognizing the limitation of using prefixed acceleration subspaces in the ECME algorithm, we propose a dynamic ECME (DECME) algorithm which allows the acceleration subspaces to be chosen dynamically. The simplest DECME implementation is what we call DECME-1, which uses the line that is determined by the two most recent est...