Multi-scale heterogeneity of geological formations is a rule, which consists of random (local-scale) and systematic (large-scale) variability of hydraulic conductivity. The random variability and depth–decaying trend, a systematic variability, have different effects on subsurface flow, thus on groundwater discharge into tunnels. Little research has examined this problem in the past. Using Monte...

We study sample covariance matrices of the form W = (1/n)CC , where C is a k × n matrix with independent and identically distributed (i.i.d.) mean 0 entries. This is a generalization of the so-calledWishart matrices, where the entries ofC are i.i.d. standard normal random variables. Such matrices arise in statistics as sample covariance matrices, and the high-dimensional case, when k is large, ...

In this paper we consider diierent aspects of robust 1-median problems on a tree network with uncertain or dynamically changing edge lengths and vertex weights which can also take negative values. The dynamic nature of a parameter is modeled by a linear function of time. A linear algorithm is designed for the absolute dynamic robust 1-median problem on a tree. The dynamic robust deviation 1-med...

Proofs of classical Chernoo-Hoeeding bounds has been used to obtain polynomial-time implementations of Spencer's derandomization method of conditional probabilities on usual-nite machine models: given m events whose complements are large deviations corresponding to weighted sums of n mutually independent Bernoulli trials, Raghavan's lattice approximation algorithm constructs for 0 ? 1 weights a...

In this paper, the high-dimensional sparse linear regression model is considered, where the overall number of variables is larger than the number of observations. We investigate the L1 penalized least absolute deviation method. Different from most of other methods, the L1 penalized LAD method does not need any knowledge of standard deviation of the noises or any moment assumptions of the noises...

We consider the learning task consisting in predicting as well as the best function in a finite reference set G up to the smallest possible additive term. If R(g) denotes the generalization error of a prediction function g, under reasonable assumptions on the loss function (typically satisfied by the least square loss when the output is bounded), it is known that the progressive mixture rule ĝ ...

We develop analytic asymptotic methods to characterize time series properties of nonlinear dynamic stochastic models. We focus on a stochastic growth model which is representative of the models underlying much of modern macroeconomics. Taking limits as the stochastic shocks become small, we derive a functional central limit theorem, a large deviation principle, and a moderate deviation principl...

By expanding functions of parton fragmentation into a heavy hadron in the inverse of the heavy quark mass m Q we attempt to factorize them into perturbative-and nonperturba-tive parts. In our approach the nonperturbative parts can be defined as matrix elements in heavy quark effective theory, the shape of the functions is predicted by perturbative QCD. In this work we neglect effect at order of...

reputation of a monetary’s authority, is an agents believe on his to control of deviation between targeting inflation and observed inflation. on one hand , a monterey’s authority, can throw agent’s trust to his polices, leading to lower inflation expectations and inflation. but on the other hand, government pressure on the monetary authority to do discretionary monetary policy( such as creation...