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作者：Bortot, P; Coles, S
作者单位：University of Bristol; University of Bologna
摘要：A recent advance in the utility of extreme value techniques has been the characterization of the extremal behaviour of Markov chains. This has enabled the application of extreme value models to series whose temporal dependence is Markovian, subject to a limitation that prevents switching between extremely high and extremely low levels. For many applications this is sufficient, but for others, most notably in the field of finance, it is common to find series in which successive values switch be...
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作者：Mao, WX; Zhao, LH
作者单位：University of Pennsylvania
摘要：We construct approximate confidence intervals for a nonparametric regression function, using polynomial splines with free-knot locations. The number of knots is determined by generalized cross-validation. The estimates of knot locations and coefficients are obtained through a non-linear least squares solution that corresponds to the maximum likelihood estimate. Confidence intervals are then constructed based on the asymptotic distribution of the maximum likelihood estimator. Average coverage p...
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作者：Robert, CP; Meng, XL; Moller, J; Rosenthal, JS; Jennison, C; Hurn, MA; Al-Awadhi, F; McCullagh, P; Andrieu, C; Doucet, A; Dellaportas, P; Papageorgiou, I; Ehlers, RS; Erosheva, EA; Fienberg, SE; Forster, JJ; Gill, RC; Friel, N; Green, P; Hastie, D; King, R; Künsch, HR; Lazar, NA; Osinski, C
作者单位：Institut Polytechnique de Paris; ENSAE Paris; Universite PSL; Universite Paris-Dauphine; Harvard University; University of Chicago; Aalborg University; University of Toronto; University of Bath; Kuwait University; University of Bristol; University of Cambridge; Athens University of Economics & Business; Universidade Federal do Parana; Carnegie Mellon University; University of Southampton; University of Glasgow; Swiss Federal Institutes of Technology Domain; ETH Zurich; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
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作者：Chiou, JM; Müller, HG; Wang, JL
作者单位：University of California System; University of California Davis; National Health Research Institutes - Taiwan
摘要：We propose a class of semiparametric functional regression models to describe the influence of vector-valued covariates on a sample of response curves. Each observed curve is viewed as the realization of a random process, composed of an overall mean function and random components. The finite dimensional covariates influence the random components of the eigenfunction expansion through single-index models that include unknown smooth link and variance functions. The parametric components of the s...
