A new noise reduction algorithm HeNLM-LA is proposed. It is a modi cation of the non-local means algorithm using Hermite functions expansion of pixel neighborhoods. The ltering strength parameter is automatically adjusted proportionally to the local noise level. An algorithm for local noise level estimation is based on edge modeling; it suppresses high-amplitude edges in the map of local image ...

In this paper a fixed design regression model where the errors follow a strictly stationary process is considered. In this model the conditional mean function and the conditional variance function are unknown curves. Correlated errors when observations are missing in the response variable are assumed. Four nonparametric estimators of the conditional variance function based on local polynomial f...

The characteristic function (chf) of a lognormal process is derived using saddle point method . Relations are established between the polar coordinates of the saddle point and variance and mean parameters. The characteristic function and cumulants are then decomposed into a primary and a secondary component. The sum rules for the variance and means of a sum of lognormals and the computation of ...

We investigate the risk-return relation in international stock markets using realized variance constructed from MSCI (Morgan Stanley Capital International) daily stock price indices. In contrast with the capital asset pricing model, realized variance by itself provides negligible information about future excess stock market returns; however, we uncover a positive and significant risk-return tra...

The spatial distribution of a natural resource is an important consideration in designing an efficient survey or monitoring program for the resource. We review a unified strategy for designing probability samples of discrete, finite resource populations, such as lakes within some geographical region; linear populations, such as a stream network in a drainage basin; and continuous, two-dimension...

Self-stabilizing local k-placement of replicas with minimal variance. Self-stabilizing algorithm for maximal graph partitioning into triangles.