-
作者：Schwarz, Katsiaryna; Krivobokova, Tatyana
作者单位：University of Gottingen
摘要：This article develops a unified framework to study the asymptotic properties of all periodic spline-based estimators, that is, of regression, penalized and smoothing splines. The explicit form of the periodic Demmler-Reinsch basis in terms of exponential splines allows the derivation of an expression for the asymptotic equivalent kernel on the real line for all spline estimators simultaneously. The corresponding bandwidth, which drives the asymptotic behaviour of spline estimators, is shown to...
-
作者：Prentice, R. L.
作者单位：Fred Hutchinson Cancer Center
摘要：The Clayton-Oakes bivariate failure time model is extended to dimensions m > 2 in a manner that allows unspecified marginal survivor functions for all dimensions less than m. Special cases that allow unspecified marginal survivor functions of dimension q or less with q < m, while making some provisions for dependencies of dimension greater than q, are also described.
-
作者：Kunihama, Tsuyoshi; Dunson, David B.
作者单位：University of Washington; University of Washington Seattle; Duke University
摘要：In many application areas, a primary focus is on assessing evidence in the data refuting the assumption of independence of Y and X conditionally on Z, with Y response variables, X predictors of interest, and Z covariates. Ideally, one would have methods available that avoid parametric assumptions, allow Y, X, Z to be random variables on arbitrary spaces with arbitrary dimension, and accommodate rapid consideration of different candidate predictors. As a formal decision-theoretic approach has c...
-
作者：Shao, Jun; Wang, Lei
作者单位：East China Normal University; University of Wisconsin System; University of Wisconsin Madison
摘要：To estimate unknown population parameters based on data having nonignorable missing values with a semiparametric exponential tilting propensity, Kim & Yu (2011) assumed that the tilting parameter is known or can be estimated from external data, in order to avoid the identifiability issue. To remove this serious limitation on the methodology, we use an instrument, i.e., a covariate related to the study variable but unrelated to the missing data propensity, to construct some estimating equations...
-
作者：Kartsonaki, Christiana; Cox, D. R.
作者单位：University of Oxford; University of Oxford
摘要：A theoretical analysis is made of the properties of various methods for comparing two distributions of survival time. The results are intended primarily to guide the choice of method of analysis for such simple comparisons as of a treatment versus a control, but the main implications are fairly general, illustrating the performance of different models in a range of conditions. For most of the models there is a parameter specifying the comparison of interest and the Fisher information per obser...
-
作者：Petersen, Alexander; Mueller, Hans-Georg
作者单位：University of California System; University of California Davis
摘要：For multivariate functional data recorded from a sample of subjects on a common domain, one is often interested in the covariance between pairs of the component functions, extending the notion of a covariance matrix for multivariate data to the functional case. A straightforward approach is to integrate the pointwise covariance matrices over the functional time domain. We generalize this approach by defining the Fr,chet integral, which depends on the metric chosen for the space of covariance m...
-
作者：Dicker, Lee H.; Zhao, Sihai D.
作者单位：Rutgers University System; Rutgers University New Brunswick; University of Illinois System; University of Illinois Urbana-Champaign
摘要：We propose new nonparametric empirical Bayes methods for high-dimensional classification. Our classifiers are designed to approximate the Bayes classifier in a hypothesized hierarchical model, where the prior distributions for the model parameters are estimated nonparametrically from the training data. As is common with nonparametric empirical Bayes, the proposed classifiers are effective in high-dimensional settings even when the underlying model parameters are in fact nonrandom. We use nonpa...
-
作者：Lunardon, N.
作者单位：University of Padua
摘要：An adjustment for marginal composite likelihoods is derived to match the second-order theory of the likelihood when inference is for a vector-valued parameter in the absence of nuisance components. The adjustment overcomes the failure of Bartlett identities for marginal composite likelihoods and leads to a Bartlett-correctable marginal composite likelihood ratio statistic.
-
作者：Broda, Simon A.; Kan, Raymond
作者单位：University of Amsterdam; University of Toronto
摘要：Inversion formulae are derived that express the density and distribution function of a ratio of random variables in terms of the joint characteristic function of the numerator and denominator. The resulting expressions are amenable to numerical evaluation and lead to simple asymptotic expansions. The expansions reduce to known results when the denominator is almost surely positive. Their accuracy is demonstrated with numerical examples.
