Influence of Ionic Strength and pH on the Limitation of Latex Microsphere Deposition Sites on Iron-oxide Coated Sand by Humic Acid

This paper advances findings of Yang et al. 2010 and reports on how slight changes in pH or Ionic strength can significantly alter particle behaviour in porous media, when humic acids have been deposited beforehand. .

Network formation under mutual consent and costly communication

We consider two different approaches to describe the formation of social networks under mutual consent and costly communication. First, we consider a network-based approach; in particular Jackson–Wolinsky’s concept of pairwise stability. Next, we discuss a non-cooperative game-theoretic approach, through a refinement of the Nash equilibria of Myerson’s consent game. This refinement, denoted as monadic stability, describes myopically forward looking behavior of the players. We show through an equivalence that the class of monadically stable networks is a strict subset of the class of pairwise stable networks that can be characterized fully by modifications of the properties defining pairwise stability.

Incorporating Higher Moments into Value at Risk Forecasting

Value-at-risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a simple approach to forecasting of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting the standard normal distribution with the first four moments, which are allowed to vary over time. In an extensive empirical study, we compare the GCE approach to other models of VaR forecasting and conclude that it provides accurate and robust estimates of the realized VaR. In spite of its simplicity, on our dataset GCE outperforms other estimates that are generated by both constant and time-varying higher-moments models.

Dynamic Density Forecasts for Multivariate Asset Returns

We propose a simple and flexible framework for forecasting the joint density of asset returns. The multinormal distribution is augmented with a polynomial in (time-varying) non-central co-moments of assets. We estimate the coefficients of the polynomial via the Method of Moments for a carefully selected set of co-moments. In an extensive empirical study, we compare the proposed model with a range of other models widely used in the literature. Employing a recently proposed as well as standard techniques to evaluate multivariate forecasts, we conclude that the augmented joint density provides highly accurate forecasts of the “negative tail” of the joint distribution.

Maximum likelihood estimation of higher-order integer-valued autoregressive processes

In this article, we extend the earlier work of Freeland and McCabe [Journal of time Series Analysis (2004) Vol. 25, pp. 701–722] and develop a general framework for maximum likelihood (ML) analysis of higher-order integer-valued autoregressive processes. Our exposition includes the case where the innovation sequence has a Poisson distribution and the thinning is binomial. A recursive representation of the transition probability of the model is proposed. Based on this transition probability, we derive expressions for the score function and the Fisher information matrix, which form the basis for ML estimation and inference. Similar to the results in Freeland and McCabe (2004), we show that the score function and the Fisher information matrix can be neatly represented as conditional expectations. Using the INAR(2) speci?cation with binomial thinning and Poisson innovations, we examine both the asymptotic e?ciency and ?nite sample properties of the ML estimator in relation to the widely used conditional least
squares (CLS) and Yule–Walker (YW) estimators. We conclude that, if the Poisson assumption can be justi?ed, there are substantial gains to be had from using ML especially when the thinning parameters are large.

Maximum likelihood estimation of higher-order integer-valued autoregressive processes

Corrigendum Vol. 30, Issue 2, 259, Article first published online: 15 MAR 2009 to correct the order of authors names: Bu R., K. Hadri, and B. McCabe.

Convergence of the iterative algorithm for a general Hammerstein system identification

The convergence of the iterative identification algorithm for a general Hammerstein system has been an open problem for a long time. In this paper, it is shown that the convergence can be achieved by incorporating a regularization procedure on the nonlinearity in addition to a normalization step on the parameters.

Labor unions and Nash bargaining using coalition formation games

In this paper we examine the properties of stable coalitions under sequential and simultaneous bargaining by competing labor unions. We do this using the Nash bargaining solution and various notions of stability, namely, Nash, coalitional, contractual and core stability. (C) 2011 Elsevier B.V. All rights reserved,

Explaining young mortality

Stochastic modeling of mortality rates focuses on fitting linear models to logarithmically adjusted mortality data from the middle or late ages. Whilst this modeling enables insurers to project mortality rates and hence price mortality products it does not provide good fit for younger aged mortality. Mortality rates below the early 20's are important to model as they give an insight into estimates of the cohort effect for more recent years of birth. It is also important given the cumulative nature of life expectancy to be able to forecast mortality improvements at all ages. When we attempt to fit existing models to a wider age range, 5-89, rather than 20-89 or 50-89, their weaknesses are revealed as the results are not satisfactory. The linear innovations in existing models are not flexible enough to capture the non-linear profile of mortality rates that we see at the lower ages. In this paper we modify an existing 4 factor model of mortality to enable better fitting to a wider age range, and using data from seven developed countries our empirical results show that the proposed model has a better fit to the actual data, is robust, and has good forecasting ability.

Hybrid image/ray-shooting UHF radio propagation predictor for populated indoor environments

A novel model for indoor wireless communication, based on a dual image and ray-shooting approach, is presented. The model, capable of improved site-specific indoor propagation prediction, considers multiple human bodies moving within the environment. In a modern office at 2.45GHz, the combined effect of pedestrian traffic and a moving receiver causes rapid temporal fading of up to 30dB.

Identification and molecular cloning of a novel amphibian Bowman Birk-type trypsin inhibitor from the skin of the Hejiang Odorous Frog; Odorrana hejiangensis.

In this study, an amphibian (Odorrana hejiangensis) skin extract was fractionated by reverse phase HPLC and fractions were screened for trypsin inhibitory activity. Using this initial approach, a novel trypsin inhibitory peptide was detected with an apparent protonated molecular mass of 1804.83Da, as determined by MALDI-TOF mass spectrometry. It was named Hejiang trypsin inhibitor (HJTI) in accordance. The primary structure of the biosynthetic precursor of HJTI was deduced from a cDNA sequence cloned from a skin-derived cDNA library. The primary structure of the encoded predicted mature active peptide was established as: GAPKGCWTKSYPPQPCS (non-protonated monoisotopic molecular mass - 1802.81Da). On the basis of this unequivocal amino acid sequence, a synthetic replicate was synthesized by solid phase Fmoc chemistry. This replicate displayed a moderately potent trypsin inhibition with a K(i) of 388nM. Bioinformatic analysis of the primary structure of this peptide indicated that it was a member of the Bowman-Birk family of protease inhibitors. The substitutions of Gln-14 and Ser-17 by Lys, resulted in an increase in cationicity and a small increase in potency to a K(i) value of 218nM. Neither HJTI nor its synthetic analog, possessed any significant antimicrobial activity.

Nash equilibria of network formation games under consent

We investigate the Nash equilibria of game theoretic models of network formation based on explicit consent in link formation. These so-called “consent models” explicitly take account of link formation costs. We provide characterizations of Nash equilibria of such consent models under both one-sided and two-sided costs of link formation. We relate these equilibrium concepts to link-based stability concepts, in particular strong link deletion proofness.