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作者：Jewell, NP; van der Laan, M; Lei, X
作者单位：University of California System; University of California Berkeley
摘要：For bivariate current status data with univariate monitoring times, the identifiable part of the joint distribution is three univariate cumulative distribution functions, namely the two marginal distributions and the bivariate cumulative distribution function evaluated on the diagonal. We show that smooth functionals of these univariate cumulative distribution functions can be efficiently estimated with easily computed nonparametric maximum likelihood estimators based on reduced data consistin...
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作者：Jones, B; West, M
作者单位：Massey University; Duke University
摘要：The covariance between two variables in a multivariate Gaussian distribution is decomposed into a sum of path weights for all paths connecting the two variables in an undirected independence graph. These weights are useful in determining which variables are important in mediating correlation between the two path endpoints. The decomposition arises in undirected Gaussian graphical models and does not require or involve any assumptions of causality. This covariance decomposition is derived using...
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作者：Tong, T; Wang, Y
作者单位：University of California System; University of California Santa Barbara
摘要：We propose a new estimator for the error variance in a nonparametric regression model. We estimate the error variance as the intercept in a simple linear regression model with squared differences of paired observations as the dependent variable and squared distances between the paired covariates as the regressor. For the special case of a one-dimensional domain with equally spaced design points, we show that our method reaches an asymptotic optimal rate which is not achieved by some existing m...
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作者：Chan, NH; Peng, L
作者单位：Chinese University of Hong Kong; University System of Georgia; Georgia Institute of Technology
摘要：The weighted least absolute deviations estimator is studied for an AR(1) process with ARCH(1) errors c, Unlike for the quasi maximum likelihood estimator, the estimator's limiting distribution is shown to be normal even when E(epsilon(4)(t)) = infinity. Furthermore, the estimator can be applied to examine the symmetry of the density of epsilon(t) and to estimate the quantity E(log vertical bar alpha + lambda(1/2)epsilon(t)vertical bar), which are of crucial importance for conducting asymptotic...
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作者：Yang, YH
作者单位：University of Minnesota System; University of Minnesota Twin Cities
摘要：A traditional approach to statistical inference is to identify the true or best model first with little or no consideration of the specific goal of inference in the model identification stage. Can the pursuit of the true model also lead to optimal regression estimation? In model selection, it is well known that BIC is consistent in selecting the true model, and AIC is minimax-rate optimal for estimating the regression function. A recent promising direction is adaptive model selection, in which...
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作者：Tsiatis, AA; Ma, YY
作者单位：North Carolina State University; North Carolina State University
摘要：A class of semiparametric estimators are proposed in the general setting of functional measurement error models. The estimators follow from estimating equations that are based on the serniparametric efficient score derived under a possibly incorrect distributional assumption for the unobserved 'measured with error' covariates. It is shown that such estimators are consistent and asymptotically normal even with misspecification and are efficient if computed under the truth. The methods are demon...
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作者：Jewell, NP; van der Laan, M
作者单位：University of California System; University of California Berkeley
摘要：In this paper, we show that the distribution function of survival times is identified, up to a one-parameter family of distribution functions, based on information from case-control current status data. With supplementary information on the population frequency of cases relative to controls, a simple weighted version of the nonparametric maximum likelihood estimator for prospective current status data provides a natural estimator for case-control samples. Following the parametric results of Sc...
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作者：Gangnon, RE; Kosorok, MR
作者单位：University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison
摘要：We present a simple sample-size formula for weighted log-rank statistics applied to clustered survival data with variable cluster sizes and arbitrary treatment assignments within clusters. This formula is based on the asymptotic normality of weighted log-rank statistics under certain local alternatives in the clustered data context. We also provide consistent variance estimators. The derived sample-size formula reduces to Schoenfeld's (1983) formula for cases of no clustering or independence w...
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作者：Goldwasser, MA; Tian, L; Wei, LJ
作者单位：Harvard University; Harvard T.H. Chan School of Public Health
摘要：Suppose that a consistent estimator for an infinite-dimensional parameter can be readily obtained via a set of estimating functions which has a 'good' local linear approximation around the true value of the parameter. However, it may be difficult to estimate the variance function of this estimator well. We show that, if the set of estimating functions evaluated at the true parameter value is 'asymptotically pivotal', then the 'fiducial' distribution of the parameter can be used to approximate ...
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作者：Konishi, S; Ando, T; Imoto, S
作者单位：Kyushu University; University of Tokyo
摘要：By extending Schwarz's (1978) basic idea we derive a Bayesian information criterion which enables us to evaluate models estimated by the maximum penalised likelihood method or the method of regularisation. The proposed criterion is applied to the choice of smoothing parameters and the number of basis functions in radial basis function network models. Monte Carlo experiments were conducted to examine the performance of the nonlinear modelling strategy of estimating the weight parameters by regu...
