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作者：Gorst-Rasmussen, Anders; Scheike, Thomas
作者单位：Aalborg University; University of Copenhagen
摘要：. In data sets with many more features than observations, independent screening based on all univariate regression models leads to a computationally convenient variable selection method. Recent efforts have shown that, in the case of generalized linear models, independent screening may suffice to capture all relevant features with high probability, even in ultrahigh dimension. It is unclear whether this formal sure screening property is attainable when the response is a right-censored survival...
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作者：Balabdaoui, Fadoua; Jankowski, Hanna; Rufibach, Kaspar; Pavlides, Marios
作者单位：Universite PSL; Universite Paris-Dauphine; York University - Canada; University of Zurich; Queens University Belfast
摘要：The assumption of log-concavity is a flexible and appealing non-parametric shape constraint in distribution modelling. In this work, we study the log-concave maximum likelihood estimator of a probability mass function. We show that the maximum likelihood estimator is strongly consistent and we derive its pointwise asymptotic theory under both the well-specified and misspecified settings. Our asymptotic results are used to calculate confidence intervals for the true log-concave probability mass...
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作者：Krivobokova, Tatyana
作者单位：University of Gottingen
摘要：There are two popular smoothing parameter selection methods for spline smoothing. First, smoothing parameters can be estimated by minimizing criteria that approximate the average mean-squared error of the regression function estimator. Second, the maximum likelihood paradigm can be employed, under the assumption that the regression function is a realization of some stochastic process. The asymptotic properties of both smoothing parameter estimators for penalized splines are studied and compare...
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作者：Ramsahai, Roland R.
作者单位：University of Cambridge
摘要：Interdependent effects are usually distinguished from statistical interaction by using the sufficient causes framework. This almost always involves expressing probability distributions as deterministic logic functions, where certain conditions invariably produce or prevent an outcome. Using an idea from the philosophy literature, that a cause is defined as an event which increases the probability of an outcome, a probabilistic sufficient causes framework is developed here. It expresses distrib...
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作者：Hughes, John; Haran, Murali
作者单位：University of Minnesota System; University of Minnesota Twin Cities; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：Non-Gaussian spatial data are very common in many disciplines. For instance, count data are common in disease mapping, and binary data are common in ecology. When fitting spatial regressions for such data, one needs to account for dependence to ensure reliable inference for the regression coefficients. The spatial generalized linear mixed model offers a very popular and flexible approach to modelling such data, but this model suffers from two major shortcomings: variance inflation due to spati...
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作者：Chopin, N.; Jacob, P. E.; Papaspiliopoulos, O.
作者单位：Institut Polytechnique de Paris; ENSAE Paris; Institut Polytechnique de Paris; ENSAE Paris; Universite PSL; Universite Paris-Dauphine; ICREA; Pompeu Fabra University
摘要：. We consider the generic problem of performing sequential Bayesian inference in a state space model with observation process y, state process x and fixed parameter . An idealized approach would be to apply the iterated batch importance sampling algorithm of Chopin. This is a sequential Monte Carlo algorithm in the -dimension, that samples values of , reweights iteratively these values by using the likelihood increments and rejuvenates the -particles through a resampling step and a Markov chai...
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作者：Kenah, Eben
作者单位：State University System of Florida; University of Florida
摘要：. The paper develops non-parametric methods based on contact intervals for the analysis of infectious disease data. The contact interval from person i to person j is the time between the onset of infectiousness in i and infectious contact from i to j, where we define infectious contact as a contact sufficient to infect a susceptible individual. The hazard function of the contact interval distribution equals the hazard of infectious contact from i to j, so it provides a summary of the evolution...
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作者：Lee, Youngjo; Bjornstad, Jan F.
作者单位：Seoul National University (SNU); Statistics Norway
摘要：To date, only frequentist, Bayesian and empirical Bayes approaches have been studied for the large-scale inference problem of testing simultaneously hundreds or thousands of hypotheses. Their derivations start with some summarizing statistics without modelling the basic responses. As a consequence testing procedures have been developed without necessarily checking model assumptions, and empirical null distributions are needed to avoid the problem of rejecting all null hypotheses when the sampl...
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作者：Cook, R. D.; Helland, I. S.; Su, Z.
作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Oslo; State University System of Florida; University of Florida
摘要：We build connections between envelopes, a recently proposed context for efficient estimation in multivariate statistics, and multivariate partial least squares (PLS) regression. In particular, we establish an envelope as the nucleus of both univariate and multivariate PLS, which opens the door to pursuing the same goals as PLS but using different envelope estimators. It is argued that a likelihood-based envelope estimator is less sensitive to the number of PLS components that are selected and ...
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作者：Fan, Jianqing; Liao, Yuan; Mincheva, Martina
作者单位：Princeton University; University System of Maryland; University of Maryland College Park; Princeton University
摘要：The paper deals with the estimation of a high dimensional covariance with a conditional sparsity structure and fast diverging eigenvalues. By assuming a sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the principal orthogonal complement thresholding method POET' to explore such an approximate factor structure with sparsity. The POET-estimator includes...
