7,256 research outputs found
Functional single index models for longitudinal data
A new single-index model that reflects the time-dynamic effects of the single
index is proposed for longitudinal and functional response data, possibly
measured with errors, for both longitudinal and time-invariant covariates. With
appropriate initial estimates of the parametric index, the proposed estimator
is shown to be -consistent and asymptotically normally distributed.
We also address the nonparametric estimation of regression functions and
provide estimates with optimal convergence rates. One advantage of the new
approach is that the same bandwidth is used to estimate both the nonparametric
mean function and the parameter in the index. The finite-sample performance for
the proposed procedure is studied numerically.Comment: Published in at http://dx.doi.org/10.1214/10-AOS845 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Covariate adjusted functional principal components analysis for longitudinal data
Classical multivariate principal component analysis has been extended to
functional data and termed functional principal component analysis (FPCA). Most
existing FPCA approaches do not accommodate covariate information, and it is
the goal of this paper to develop two methods that do. In the first approach,
both the mean and covariance functions depend on the covariate and time
scale while in the second approach only the mean function depends on the
covariate . Both new approaches accommodate additional measurement errors
and functional data sampled at regular time grids as well as sparse
longitudinal data sampled at irregular time grids. The first approach to fully
adjust both the mean and covariance functions adapts more to the data but is
computationally more intensive than the approach to adjust the covariate
effects on the mean function only. We develop general asymptotic theory for
both approaches and compare their performance numerically through simulation
studies and a data set.Comment: Published in at http://dx.doi.org/10.1214/09-AOS742 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
A review of Tourism Supply Chain based on the Perspective of Sustainable Development
In this paper, the theory of traditional manufacturing supply chain management is applied to the study of tourism supply chain. Based on the view of sustainable development, a large-scale relevant literature review concerning tourism supply chain and sustainable supply chain is performed, in which current situation and deficiency are reviewed. In order to solve the problem, this paper tries to discuss and establish a new sustainable supply chain pattern, in which tourist attractions are taken as core enterprises. Furthermore, this paper tries to find an optimization strategy to do facilitate long-term sustainable development of tourism and improve the tourism industry profitability and competitiveness Keywords: tourism supply chain, sustainable development, core enterpris
Inverse regression for longitudinal data
Sliced inverse regression (Duan and Li [Ann. Statist. 19 (1991) 505-530], Li
[J. Amer. Statist. Assoc. 86 (1991) 316-342]) is an appealing dimension
reduction method for regression models with multivariate covariates. It has
been extended by Ferr\'{e} and Yao [Statistics 37 (2003) 475-488, Statist.
Sinica 15 (2005) 665-683] and Hsing and Ren [Ann. Statist. 37 (2009) 726-755]
to functional covariates where the whole trajectories of random functional
covariates are completely observed. The focus of this paper is to develop
sliced inverse regression for intermittently and sparsely measured longitudinal
covariates. We develop asymptotic theory for the new procedure and show, under
some regularity conditions, that the estimated directions attain the optimal
rate of convergence. Simulation studies and data analysis are also provided to
demonstrate the performance of our method.Comment: Published in at http://dx.doi.org/10.1214/13-AOS1193 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org). With Correction
Confined Multilamellae Prefer Cylindrical Morphology
By evaporating a drop of lipid dispersion we generate the myelin morphology
often seen in dissolving surfactant powders. We explain these puzzling
nonequilibrium structures using a geometric argument: The bilayer repeat
spacing increases and thus the repulsion between bilayers decreases when a
multilamellar disk is converted into a myelin without gain or loss of material
and with number of bilayers unchanged. Sufficient reduction in bilayer
repulsion can compensate for the cost in curvature energy, leading to a net
stability of the myelin structure. A numerical estimate predicts the degree of
dehydration required to favor myelin structures over flat lamellae.Comment: 6 pages, 3 figures, submitted to Euro. Phys. J.
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