We consider the problem of testing monotonicity of the regression function in a standard nonparametric regression model. We introduce test statistics that are functionals of a certain natural U-process. We study the limiting distribution of these test statistics through strong approximation methods and the extreme value theory for Gaussian processes. We show that the tests are consistent agains...

We prove a uniform functional law of the logarithm for the local empirical process. To accomplish this we combine techniques from classical and abstract empirical process theory, Gaussian distributional approximation and probability on Banach spaces. The body of techniques we develop should prove useful to the study of the strong consistency of d-variate kernel-type nonparametric function estim...

We consider the problem of testing monotonicity of the regression function in a nonparametric regression model. We introduce test statistics that are functionals of a certain natural U-process. We study the limiting distribution of these test statistics through strong approximation methods and the extreme value theory for Gaussian processes. We show that the tests are consistent against general...

We introduce strong convergence in regard to approximation of copulas. This new type of convergence is useful in dealing with the-product of Darsow, Nguyen, and Olsen for copulas. We also provide tools for constructing strong approximations of copulas by using partitions of unity.

We provide a joint strong approximation of the uniform spacings empirical pro1 cess and of the uniform quantile process by sequences of independent Gaussian processes. 2 This allows us to obtain an explicit description of the limiting Gaussian process generated by 3 the sample spacings from a non-uniform distribution. It is of the form B(t)+ (1− σF ){(1− 4 t) log(1 − t)} ∫ 1 0 {B(s)/(1 − s)}ds,...

The dynamics of an ensemble of bistable elements under the influence of noise and with global time-delayed coupling is studied numerically by using a Langevin description and analytically by using 1) a Gaussian approximation and 2) a dichotomic model. We find that for a strong enough positive feedback the system undergoes a phase transition and adopts a non-zero stationary mean field. A variety...

We propose the frozen Gaussian approximation for computation of high frequency wave propagation. This method approximates the solution to the wave equation by an integral representation. It provides a highly efficient computational tool based on the asymptotic analysis on phase plane. Compared to geometric optics, it provides a valid solution around caustics. Compared to the Gaussian beam metho...

In many applications, one has to actively select among a set of expensive observations before making an informed decision. Often, we want to select observations which perform well when evaluated with an objective function chosen by an adversary. Examples include minimizing the maximum posterior variance in Gaussian Process regression, robust experimental design, and sensor placement for outbrea...