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作者：Henmi, M; Eguchi, S
作者单位：University of Warwick; Graduate University for Advanced Studies - Japan; Research Organization of Information & Systems (ROIS); Institute of Statistical Mathematics (ISM) - Japan
摘要：This paper is concerned with a paradox associated with parameter estimation in the presence of nuisance parameters. In a statistical model with unknown nuisance parameters, the efficiency of an estimator of a parameter usually increases when the nuisance parameters are known. However the opposite phenomenon can sometimes occur. In this paper, we elucidate the occurrence of this paradox by examining estimating functions. In particular, we focus on the projected estimating function, which is def...
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作者：Wang, YCJ
作者单位：Rutgers University System; Rutgers University Camden; Rutgers University New Brunswick
摘要：In the Lancaster representation a joint density is decomposed into a sum of additive interactions. Using these interactions, we derive conditions for checking compatibility among a collection of marginal densities. The representation also shows bow to construct an all-positive joint density additively from a given set of compatible marginals. An algorithm is proposed for reducing the dimension of the marginal densities so that compatibility can be checked in sequential increments. The represen...
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作者：Jin, ZZ; Lin, DY; Wei, LJ; Ying, ZL
作者单位：Columbia University; Columbia University; Harvard University; University of North Carolina; University of North Carolina Chapel Hill
摘要：A broad class of rank-based monotone estimating functions is developed for the semi-parametric accelerated failure time model with censored observations. The corresponding estimators can be obtained via linear programming, and are shown to be consistent and asymptotically normal. The limiting covariance matrices can be estimated by a resampling technique, which does not involve nonparametric density estimation or numerical derivatives. The new estimators represent consistent roots of the non-m...
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作者：Cui, HJ; He, XM; Ng, KW
作者单位：Beijing Normal University; University of Illinois System; University of Illinois Urbana-Champaign; University of Hong Kong
摘要：Algebraically, principal components can be defined as the eigenvalues and eigenvectors of a covariance or correlation matrix, but they are statistically meaningful as successive projections of the multivariate data in the direction of maximal variability. An attractive alternative in robust principal component analysis is to replace the classical variability measure, i.e. variance, by a robust dispersion measure. This projection-pursuit approach was first proposed in Li & Chen (1985) as a meth...
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作者：Davis, RA; Dunsmuir, WTM; Streett, SB
作者单位：Colorado State University System; Colorado State University Fort Collins; University of New South Wales Sydney; National Center Atmospheric Research (NCAR) - USA
摘要：This paper is concerned with a general class of observation-driven models for time series of counts whose conditional distributions given past observations and explanatory variables follow a Poisson distribution. These models provide a flexible framework for modelling a wide range of dependence structures. Conditions for stationarity and ergodicity of these processes are established from which the large-sample properties of the maximum likelihood estimators can be derived. Simulations are prov...
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作者：Broemeling, L; Broemeling, A
作者单位：University of Texas System; UTMD Anderson Cancer Center
摘要：The contributions of Ernest Lhoste are largely unknown outside France, and even within that country are not well known. His important contributions were in the two areas of the development of prior distributions that represent little or no information, and a sophisticated posterior analysis for normal and binomial populations. His results are similar to those of Haldane (1948) and Jeffreys (1961), but they appeared much earlier, in 1923. He gave a great deal of thought to how to represent vagu...
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作者：Robins, JM; Scheines, R; Spirtes, P; Wasserman, L
作者单位：Harvard University; Carnegie Mellon University; Carnegie Mellon University
摘要：There is a long tradition of representing causal relationships by directed acyclic graphs (Wright, 1934). Spirtes (1994), Spirtes et al. ( 1993) and Pearl & Verma (1991) describe procedures for inferring the presence or absence of causal arrows in the graph even if there might be unobserved confounding variables, and/or an unknown time order, and that under weak conditions, for certain combinations of directed acyclic graphs and probability distributions, are asymptotically, in sample size, co...
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作者：Fried, R; Didelez, V
作者单位：Dortmund University of Technology; University of London; University College London
摘要：We derive conditions for decomposition and collapsibility of graphical interaction models for multivariate time series. These properties enable us to perform stepwise model selection under certain restrictions. For illustration, we apply the results to a multivariate time series describing the haemodynamic system as monitored in intensive care.
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作者：Wong, F; Carter, CK; Kohn, R
作者单位：University of New South Wales Sydney; Commonwealth Scientific & Industrial Research Organisation (CSIRO); University of New South Wales Sydney
摘要：A Bayesian method is proposed for estimating an inverse covariance matrix from Gaussian data. The method is based on a prior that allows the off-diagonal elements of the inverse covariance matrix to be zero, and in many applications results in a parsimonious parameterisation of the covariance matrix. No assumption is made about the structure of the corresponding graphical model, so the method applies to both nondecomposable and decomposable graphs. All the parameters are estimated by model ave...
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作者：Gaetan, C; Yao, JF
作者单位：University of Padua; Universite de Rennes
摘要：In this paper we introduce a new stochastic variant of the EM algorithm. The algorithm combines the principle of multiple imputation and the theory of simulated annealing to deal with cases where the E-step and the M-step can be intractable or numerically inefficient.
