We study distributed estimation of a high-dimensional static parameter vector through group sensors whose communication network is modeled by fixed directed graph. Different from existing time-triggered schemes, an event-triggered asynchronous scheme investigated in order to reduce while preserving convergence. A algorithm with single step size first proposed based on time-dependent decaying th...

We study nonparametric maximum likelihood estimation of a log–concave probability density and its distribution and hazard function. Some general properties of these estimators are derived from two characterizations. It is shown that the rate of convergence with respect to supremum norm on a compact interval for the density and hazard rate estimator is at least (log(n)/n) and typically (log(n)/n...

A procedure is described for estimating evolutionary rate matrices from observed site frequency data. The procedure assumes (1) that the data are obtained from a constant size population evolving according to a stationary Wright-Fisher or decoupled Moran model; (2) that the data consist of a multiple alignment of a moderate number of sequenced genomes drawn randomly from the population; and (3)...