Five-dimensional metric f(R)f(R) gravity and the accelerated universe

The metric $f(R)$ theories of gravity are generalized to five-dimensional spacetimes. By assuming a hypersurface-orthogonal Killing vector field representing the compact fifth dimension, the five-dimensional theories are reduced to their four-dimensional formalism. Then we study the cosmology of a special class of $f(R)=\alpha R^m$ models in a spatially flat FRW spacetime. It is shown that the parameter $m$ can be constrained to a certain range by the current observed deceleration parameter, and its lower bound corresponds to the Kaluza-Klein theory. It turns out that both expansion and contraction of the extra dimension may prescribe the smooth transition from the deceleration era to the acceleration era in the recent past as well as an accelerated scenario for the present universe. Hence five-dimensional $f(R)$ gravity can naturally account for the present accelerated expansion of the universe. Moreover, the models predict a transition from acceleration to deceleration in the future, followed by a cosmic recollapse within finite time. This differs from the prediction of the five-dimensional Brans-Dicke theory but is in consistent with a recent prediction based on loop quantum cosmology.Comment: 14 pages, 9 figures; Version published in PR

On the Radiatively Induced Lorentz and CPT Violating Chern-Simons Term

The radiatively induced Lorentz and CPT violating Chern-Simons terms in QED is calculated based on the recently developed loop regularization method [Y.L. Wu, Int.J.Mod.Phys.A18 (2003) 5363, hep-th/0209021; Y.L. Wu, Mod.Phys.Lett.A19 (2004) 2191, hep-th/0311082] for quantum field theories. It enables us to make general comments on the various results in literature and obtain a consistent result when simultaneously combining the evaluation for the chiral anomaly which has a unique form once the vector current is kept conserved.Comment: 10 pages, no figures, published versio

A simultaneous confidence band for sparse longitudinal regression

Functional data analysis has received considerable recent attention and a number of successful applications have been reported. In this paper, asymptotically simultaneous confidence bands are obtained for the mean function of the functional regression model, using piecewise constant spline estimation. Simulation experiments corroborate the asymptotic theory. The confidence band procedure is illustrated by analyzing CD4 cell counts of HIV infected patients

Dimension reduction and estimation in the secondary analysis of case-control studies

© 2018, Institute of Mathematical Statistics. All rights reserved. Studying the relationship between covariates based on retrospective data is the main purpose of secondary analysis, an area of increasing interest. We examine the secondary analysis problem when multiple covariates are available, while only a regression mean model is specified. Despite the completely parametric modeling of the regression mean function, the case-control nature of the data requires special treatment and semiparametric efficient estimation generates various nonparametric estimation problems with multivariate covariates. We devise a dimension reduction approach that fits with the specified primary and secondary models in the original problem setting, and use reweighting to adjust for the case-control nature of the data, even when the disease rate in the source population is unknown. The resulting estimator is both locally efficient and robust against the misspecification of the regression error distribution, which can be heteroscedastic as well as non-Gaussian. We demonstrate the advantage of our method over several existing methods, both analytically and numerically

A three-by-three matrix spectral problem for AKNS hierarchy and its binary Nonlinearization

A three-by-three matrix spectral problem for AKNS soliton hierarchy is proposed and the corresponding Bargmann symmetry constraint involved in Lax pairs and adjoint Lax pairs is discussed. The resulting nonlinearized Lax systems possess classical Hamiltonian structures, in which the nonlinearized spatial system is intimately related to stationary AKNS flows. These nonlinearized Lax systems also lead to a sort of involutive solutions to each AKNS soliton equation.Comment: 21pages, in Late

Estimation and inference of error-prone covariate effect in the presence of confounding variables

© 2017, Institute of Mathematical Statistics. All rights reserved. We introduce a general single index semiparametric measurement error model for the case that the main covariate of interest is measured with error and modeled parametrically, and where there are many other variables also important to the modeling. We propose a semiparametric bias-correction approach to estimate the effect of the covariate of interest. The resultant estimators are shown to be root-n consistent, asymptotically normal and locally efficient. Comprehensive simulations and an analysis of an empirical data set are performed to demonstrate the finite sample performance and the bias reduction of the locally efficient estimators