A review on some classes of algebraic systems

ABSTRACT

In this paper, we review some algebraic control system. Precisely, linear and bilinear systems on Euclidean spaces and invariant and linear systems on Lie groups. The fourth classes of systems have a common issue: to any class, there exists an associated subgroup. From this object, we survey the controllability property. Especially, from those coming from our contribution to the theory.     

VaR and ES for linear portfolios with mixture of elliptic distributions risk factors

In this paper, we generalize the Linear VaR method from portfolios with normally distributed risk factors to portfolios with mixture of elliptically distributed ones. We treat both the Expected Shortfall and the Value-at-Risk of such portfolios. Special attention is given to the particular case of a mixture of multivariate t-distributions. This is a part of J. SADEFO-KAMDEM PhD Thesis[12] of the Université de Reims, France . It has been presented at the workshop on modelling and computation in Financial Engineering at Bad Herrenalb, Germany May 6-8, 2003. The author is an associate professor at the Department of mathematics, université d’Evry Val d’Essonne.     

On the recent papers by Nagode et al.

The recent work Professor Nagode and colleagues is discussed with respect to the use of mixture Weibull models.     

二次型时频分析技术的开发与应用

基于二次型的时频分析是高分辨率时频分析技术的有效方法之一，该项技术能够有效反映时变信号的频谱特性，具有分辨率高、能量集中和跟踪瞬时频率的特点。从时变信号的特点出发，阐述了二次型时频分析技术的基本方法原理，采用正演模型分析验证了该方法的有效性，并在实际地震资料中应用于识别物源方向、划分沉积相带、预测储层结构以及相对厚度等诸多方面，均取得了较好的效果。     

Inference for pth‐order random coefficient integer‐valued autoregressive processes

Abstract. A pth‐order random coefficient integer‐valued autoregressive [RCINAR(p)] model is proposed for count data. Stationarity and ergodicity properties are established. Maximum likelihood, conditional least squares, modified quasi‐likelihood and generalized method of moments are used to estimate the model parameters. Asymptotic properties of the estimators are derived. Simulation results on the comparison of the estimators are reported. The models are applied to two real data sets.     

Almost k-wise independence versus k-wise independence

We say that a distribution over {0,1}ⁿ is (ε,k)-wise independent if its restriction to every k coordinates results in a distribution that is ε-close to the uniform distribution. A natural question regarding (ε,k)-wise independent distributions is how close they are to some k-wise independent distribution. We show that there exist (ε,k)-wise independent distributions whose statistical distance is at least n^O(k)·ε from any k-wise independent distribution. In addition, we show that for any (ε,k)-wise independent distribution there exists some k-wise independent distribution, whose statistical distance is n^O(k)·ε.     

Synthesis and characterization of acidic properties of Al-SBA-15 materials with varying Si/Al ratios

Al-SBA-15 of varying Si/Al ratios in the range 11.4–78.4 was synthesized using tri-block copolymer P123. The calcined materials were examined by XRD, pore size distribution, surface area, ²⁷Al NMR spectroscopy. The acidity and acid strength distribution were studied using microcalorimetric adsorption of NH₃. The acidic properties were also examined by cumene cracking reaction as a function of Si/Al ratios. Systematic variation of acidity and activity was observed as a function of Si/Al ratio. The initial heats of NH₃ adsorption correlated well with activity indicate that acid sites with ΔH > 100 kJ/mole is responsible for cumene cracking activity. Linear correlations were obtained with total acidity and cumene cracking activities. The tetrahedral aluminum was found to be responsible for the observed acidities and catalytic activities.     

Parametric and nonparametric Bayesian model specification: A case study involving models for count data

In this paper we present the results of a simulation study to explore the ability of Bayesian parametric and nonparametric models to provide an adequate fit to count data of the type that would routinely be analyzed parametrically either through fixed-effects or random-effects Poisson models. The context of the study is a randomized controlled trial with two groups (treatment and control). Our nonparametric approach uses several modeling formulations based on Dirichlet process priors. We find that the nonparametric models are able to flexibly adapt to the data, to offer rich posterior inference, and to provide, in a variety of settings, more accurate predictive inference than parametric models.     

Mean-square stability for discrete bilinear systems in Hilbert space

A discrete system is uniformly mean-square stable if uniform convergence is preserved between input and state correlation sequences, and if nuclearity is preserved between the input and state correlation limits. This paper supplies a contraction-free condition ensuring mean-square stability for infinite-dimensional bilinear systems evolving in a separable Hilbert space.     

Identification environment and robust forecasting for nonlinear time series

In this paper, the methods of time series for nonlinearity are briefly surveyed, with particular attention paid to a new test design based on a neural network specification. The proposed integrated expert system contains two main components: an identification environment and a robust forecasting design. The identification environment can be viewed as a integrated dynamic design in which cognitive capabilities arise as a direct consequence of their self-organizational properties. The integrated framework used for discussing the similarities and differences in the nonlinear time series behavior is presented. Moreover, its performance in prediction proves to be superior than the former work. For the investigation of robust forecasting, we perform a simulation study to demonstrate the applicability and the forecasting performance.