the purpose of this paper is to provide some asymptotic results for nonparametric estimator of the lorenz curve and lorenz process for the case in which data are assumed to be strong mixing subject to random left truncation. first, we show that nonparametric estimator of the lorenz curve is uniformly strongly consistent for the associated lorenz curve. also, a strong gaussian approximation for ...

The purpose of this paper is to provide some asymptotic results for nonparametric estimator of the Lorenz curve and Lorenz process for the case in which data are assumed to be strong mixing subject to random left truncation. First, we show that nonparametric estimator of the Lorenz curve is uniformly strongly consistent for the associated Lorenz curve. Also, a strong Gaussian approximation for ...

In a seminal paper, Page found the exact formula for average entanglement entropy pure random state. We consider analogous problem ensemble of fermionic Gaussian states, which plays crucial role in context free Hamiltonians. Using recent results from matrix theory, we show that states subsystem $N_A$ out $N$ degrees freedom is given by $\langle S_A\rangle_\mathrm{G}\!=\!(N\!-\!\tfrac{1}{2})\Psi...

background: the area of contaminated lands exposed to the health risk of environmental pollutants is a matter of argument. in this study, a new method was developed to estimate the amount of area that is exposed to higher than normal levels of cr, mn, and v. methods: overall, 170 soil samples were collected from the upper 10 cm of soil in an arid area in central part of iran in semnan province....

BACKGROUND AND PURPOSE Pre-treatment ADC characteristics have been shown to predict response to bevacizumab in recurrent glioblastoma multiforme. However, no studies have examined whether ADC characteristics are specific to this particular treatment. The purpose of the current study was to determine whether ADC histogram analysis is a bevacizumab-specific or treatment-independent biomarker of t...

Fitting a Gaussian curve to real settlement data is of practical use because the parameters that describe the curve, namely volume loss, maximum settlement and trough width, are conceptually easy to understand and can be compared at different locations and for different tunnel sizes, depths and construction methods. Where the magnitude of surface settlements is small, it can be difficult to obt...

Gaussian Mixture Models (GMM) have been broadly applied for the fitting of probability density function. However, due to the intrinsic linearity of GMM, usually many components are needed to appropriately fit the data distribution, when there are curve manifolds in the data cloud. In order to solve this problem and represent data with curve manifolds better, in this paper we propose a new nonli...