On the effect of prior assumptions in Bayesian model averaging with applications to growth regression

This paper examines the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. The paper analyzes the effect of a variety of prior assumptions on the inference concerning model size, posterior inclusion probabilities of regressors, and predictive performance. The analysis illustrates these issues in the context of cross-country growth regressions using three datasets with 41 to 67 potential drivers of growth and 72 to 93 observations. The results favor particular prior structures for use in this and related contexts.Educational Technology and Distance Education,Geographical Information Systems,Statistical&Mathematical Sciences,Science Education,Scientific Research&Science Parks

Nonlocal First-Order Hamilton-Jacobi Equations Modelling Dislocations Dynamics

We study nonlocal first-order equations arising in the theory of dislocations. We prove the existence and uniqueness of the solutions of these equations in the case of positive and negative velocities, under suitable regularity assumptions on the initial data and the velocity. These results are based on new $L^1$-type estimates on the viscosity solutions of first-order Hamilton-Jacobi Equations appearing in the so-called ``level-sets approach''. Our work is inspired by and simplifies a recent work of Alvarez, Cardaliaguet and Monneau

Jointness in Bayesian variable selection with applications to growth regression

The authors present a measure of jointness to explore dependence among regressors in the context of Bayesian model selection. The jointness measure they propose equals the posterior odds ratio between those models that include a set of variables and the models that only include proper subsets. They show its application in cross-country growth regressions using two data-sets from the model-averaging growth literature.Statistical&Mathematical Sciences,Climate Change,Educational Technology and Distance Education,Economic Theory&Research,Achieving Shared Growth

Benchmark priors for Bayesian models averaging

In contrast to a posterior analysis given a particular sampling model, posterior model probabilities in the context of model uncertainty are typically rather sensitive to the specification of the prior. In particular, 'diffuse' priors on model-specific parameters can lead to quite unexpected consequences. Here we focus on the practically relevant situation where we need to entertain a (large) number of sampling models and we have (or wish to use) little or no subjective prior information. We aim at providing an 'automatic' or 'benchmark' prior structure that can be used in such cases. We focus on the Normal linear regression model with uncertainty in the choice of regressors. We propose a partly noninformative prior structure related to a Natural Conjugate $g$-prior specification, where the amount of subjective information requested from the user is limited to the choice of a single scalar hyperparameter $g_{0j}$. The consequences of different choices for $g_{0j}$ are examined. We investigate theoretical properties, such as consistency of the implied Bayesian procedure. Links with classical information criteria are provided. In addition, we examine the finite sample implications of several choices of $g_{0j}$ in a simulation study. The use of the MC$^3$ algorithm of Madigan and York (1995), combined with efficient coding in Fortran, makes it feasible to conduct large simulations. In addition to posterior criteria, we shall also compare the predictive performance of different priors. A classic example concerning the economics of crime will also be provided and contrasted with results in the literature. The main findings of the paper will lead us to propose a 'benchmark' prior specification in a linear regression context with model uncertainty.Bayes factors, Markov chain, Monte Carlo, Posterior odds, Prior elicitation

Global Existence Results and Uniqueness for Dislocation Equations

We are interested in nonlocal Eikonal Equations arising in the study of the dynamics of dislocations lines in crystals. For these nonlocal but also non monotone equations, only the existence and uniqueness of Lipschitz and local-in-time solutions were available in some particular cases. In this paper, we propose a definition of weak solutions for which we are able to prove the existence for all time. Then we discuss the uniqueness of such solutions in several situations, both in the monotone and non monotone case

Two new species of Cephalobidae from Valle de la Luna, Argentina, and observations on the genera Acrobeles and Nothacrobeles (Nematoda : Rhabditida)

Description est donnée d'#Acrobeles emmatus sp. n. et de #Nothacrobeles lunensis sp. n. provenant d'une vallée désertique d'Argentine. #A. emmatus sp. n. se distingue de toutes les autres espèces connues du genre par la présence d'une "couche interne" de la cuticule montrant deux ondulations par anneau. #N. lunensis sp. n. se différencie de toutes les autres espèces du genre par sa "double cuticule", semblable à celle observée chez #Seleborca et #Triligulla. Il est avancé que ce type de structure cuticulaire peut être apparu indépendamment dans au moins trois lignées et qu'il est donc insuffisant pour représenter un caractère générique. En conséquence, #Seleborca et #Triligulla sont proposés comme des synonymes mineurs d'#Acrobeles et #Cervidellus, respectivement. Un unique mâle de #Nothacrobeles cf. #subtilis est également décrit. Ses proboles sont pourvues de minuscules excroissances et le champ latéral est composé de quatre lignes antérieurement et de trois postérieurement. Ce caractère est considéré comme invalidant le genre #Namibinema qui est donc proposé comme synonyme mineur de #Nothacrobeles. Les diagnoses des genres #Acrobeles et #Nothacrobeles sont amendées et un tableau des caractères spécifiques différentiels est donné pour chacun des deux genres. (Résumé d'auteur

Total synthesis and biological evaluation of the tetramic acid based natural product harzianic acid and its stereoisomers

Financial support for this project was provided by Cancer Research UK (Grant No. C21383/A6950)The bioactive natural product harzianic acid was prepared for the first time in just six steps (longest linear sequence) with an overall yield of 22%. The identification of conditions to telescope amide bond formation and a Lacey-Dieckmann reaction into one pot proved important. The three stereoisomers of harzianic acid were also prepared, providing material for comparison of their biological activity. While all of the isomers promoted root growth, improved antifungal activity was unexpectedly associated with isomers in the enantiomeric series opposite that of harzianic acid.Publisher PDFPeer reviewe

Dynamics of in silico leukocyte rolling, activation, and adhesion

BACKGROUND: We present a multilevel, agent based, in silico model that represents the dynamics of rolling, activation, and adhesion of individual leukocytes in vitro. Object-oriented software components were designed, verified, plugged together, and then operated in ways that represent the molecular and cellular mechanisms believed responsible for leukocyte rolling and adhesion. The result is an in silico analogue of an experimental in vitro system. The experimentally measured, phenotypic attributes of the analogue were compared and contrasted to those of leukocytes in vitro from three different experimental conditions. RESULTS: The individual in silico dynamics of "rolling" on simulated P-selectin, and separately on simulated VCAM-1, were an acceptable match to individual in vitro distance-time and velocity-time measurements. The analogues are also able to represent the transition from rolling to adhesion on P-selectin and VCAM-1 in the presence of GRO-α chemokine. The individual in silico and in vitro behavioral similarities translated successfully to population level measures. These behavioral similarities were enabled in part by subdividing the functionality of the analogue's surface into 600 independent, "cell"-controlled, equally capable modules of comparable functionality. CONCLUSION: The overlap in phenotypic attributes of our analogue with those of leukocytes in vitro confirm the considerable potential of our model for studying the key events that determine the behavioral outcome of individual leukocytes during rolling, activation, and adhesion. Our results provide an important foundation and framework for future in silico research into plausible causal links between well-documented, subcellular molecular level events and the variety of systemic phenotypic attributes that distinguish normal leukocyte adhesion from abnormal disease-associated adhesion