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作者：Carvalho, C. M.; Scott, J. G.
作者单位：University of Chicago; Duke University
摘要：This paper presents a default model-selection procedure for Gaussian graphical models that involves two new developments. First, we develop a default version of the hyper-inverse Wishart prior for restricted covariance matrices, called the hyper-inverse Wishart g-prior, and show how it corresponds to the implied fractional prior for selecting a graph using fractional Bayes factors. Second, we apply a class of priors that automatically handles the problem of multiple hypothesis testing. We demo...
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作者：Goga, C.; Deville, J-C.; Ruiz-Gazen, A.
作者单位：Universite Bourgogne Europe; Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI); Universite de Toulouse; Universite Toulouse 1 Capitole; Toulouse School of Economics
摘要：An important problem associated with two-sample surveys is the estimation of nonlinear functions of finite population totals such as ratios, correlation coefficients or measures of income inequality. Computation and estimation of the variance of such complex statistics are made more difficult by the existence of overlapping units. In one-sample surveys, the linearization method based on the influence function approach is a powerful tool for variance estimation. We introduce a two-sample linear...
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作者：Tsai, Wei Yann
作者单位：Columbia University
摘要：We obtain a pseudo-partial likelihood for proportional hazards models with biased-sampling data by embedding the biased-sampling data into left-truncated data. The log pseudo-partial likelihood of the biased-sampling data is the expectation of the log partial likelihood of the left-truncated data conditioned on the observed data. In addition, asymptotic properties of the estimator that maximize the pseudo-partial likelihood are derived. Applications to length-biased data, biased samples with r...
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作者：Kou, S. C.; McCullagh, P.
作者单位：Harvard University; University of Chicago
摘要：The standard matrix permanent is the solution to a number of combinatorial and graph-theoretic problems, and the alpha-weighted permanent is the density function for a class of Cox processes called boson processes. The exact computation of the ordinary permanent is known to be #P-complete, and the same appears to be the case for the alpha-permanent for most values of alpha. At present, the lack of a satisfactory algorithm for approximating the alpha-permanent is a formidable obstacle to the us...
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作者：Johnson, Lynn M.; Strawderman, Robert L.
作者单位：Cornell University; Cornell University
摘要：This paper extends the induced smoothing procedure of Brown & Wang (2006) for the semiparametric accelerated failure time model to the case of clustered failure time data. The resulting procedure permits fast and accurate computation of regression parameter estimates and standard errors using simple and widely available numerical methods, such as the Newton-Raphson algorithm. The regression parameter estimates are shown to be strongly consistent and asymptotically normal; in addition, we prove...
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作者：Chen, Song Xi; Peng, Liang; Qin, Ying-Li
作者单位：Iowa State University; University System of Georgia; Georgia Institute of Technology
摘要：We evaluate the effects of data dimension on the asymptotic normality of the empirical likelihood ratio for high-dimensional data under a general multivariate model. Data dimension and dependence among components of the multivariate random vector affect the empirical likelihood directly through the trace and the eigenvalues of the covariance matrix. The growth rates to infinity we obtain for the data dimension improve the rates of Hjort et al. (2008).
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作者：Conti, S.; Gosling, J. P.; Oakley, J. E.; O'Hagan, A.
作者单位：Health Protection Agency; Food & Environment Research Agency; University of Sheffield
摘要：Computer codes are used in scientific research to study and predict the behaviour of complex systems. Their run times often make uncertainty and sensitivity analyses impractical because of the thousands of runs that are conventionally required, so efficient techniques have been developed based on a statistical representation of the code. The approach is less straightforward for dynamic codes, which represent time-evolving systems. We develop a novel iterative system to build a statistical mode...
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作者：Chernozhukov, V.; Fernandez-Val, I.; Galichon, A.
作者单位：Massachusetts Institute of Technology (MIT); Boston University; Institut Polytechnique de Paris; Ecole Polytechnique
摘要：Suppose that a target function is monotonic and an available original estimate of this target function is not monotonic. Rearrangements, univariate and multivariate, transform the original estimate to a monotonic estimate that always lies closer in common metrics to the target function. Furthermore, suppose an original confidence interval, which covers the target function with probability at least 1-alpha, is defined by an upper and lower endpoint functions that are not monotonic. Then the rea...
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作者：Beerenwinkel, N.; Sullivant, S.
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich; North Carolina State University
摘要：We introduce and analyze a waiting time model for the accumulation of genetic changes. The continuous-time conjunctive Bayesian network is defined by a partially ordered set of mutations and by the rate of fixation of each mutation. The partial order encodes constraints on the order in which mutations can fixate in the population, shedding light on the mutational pathways underlying the evolutionary process. We study a censored version of the model and derive equations for an em algorithm to p...
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作者：Luo, Xiaodong; Tsai, Wei Yann; Xu, Qiang
作者单位：Icahn School of Medicine at Mount Sinai; Columbia University; US Food & Drug Administration (FDA)
摘要：By embedding the missing covariate data into a left-truncated and right-censored survival model, we propose a new class of weighted estimating functions for the Cox regression model with missing covariates. The resulting estimators, called the pseudo-partial likelihood estimators, are shown to be consistent and asymptotically normal. A simulation study demonstrates that, compared with the popular inverse-probability weighted estimators, the new estimators perform better when the observation pr...
