Discussion of: Statistical analysis of an archeological find

Discussion of ``Statistical analysis of an archeological find'' by Andrey Feuerverger [arXiv:0804.0079]Comment: Published in at http://dx.doi.org/10.1214/08-AOAS99F the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Graphical chain models for the analysis of complex genetic diseases: an application to hypertension

A crucial task in modern genetic medicine is the understanding of complex genetic diseases. The main complicating features are that a combination of genetic and environmental risk factors is involved, and the phenotype of interest may be complex. Traditional statistical techniques based on lod-scores fail when the disease is no longer monogenic and the underlying disease transmission model is not defined. Different kinds of association tests have been proved to be an appropriate and powerful statistical tool to detect a candidate gene for a complex disorder. However, statistical techniques able to investigate direct and indirect influences among phenotypes, genotypes and environmental risk factors, are required to analyse the association structure of complex diseases. In this paper we propose graphical models as a natural tool to analyse the multifactorial structure of complex genetic diseases. An application of this model to primary hypertension data set is illustrated

Global Value Chains During the Great Trade Collapse: A Bullwhip Effect?

This paper analyzes the performance of global value chains during the trade collapse. To do so, it exploits a unique transaction-level dataset on French firms containing information on cross-border monthly transactions matched with data on worldwide intra-.rm linkages as defined by property rights (multinational business groups, hierarchies of firms). This newly assembled dataset allows us to distinguish firm-level transactions among two alternative organizational modes of global value chains: internalization of activities (intra- group trade/trade among related parties) or establishment of supply contracts (arm's length trade/trade among unrelated parties). After an overall assessment of the role of global value chains during the trade collapse, we document that intra-group trade in intermediates was characterized by a faster drop followed by a faster recovery than arm's length trade. Amplified fluctuations in terms of trade elasticities by value chains have been referred to as the "bullwhip effect" and have been attributed to the adjustment of inventories within supply chains. In this paper we first con.rm the existence of such an effect due to trade in inter- mediates, and we underline the role that different organizational modes can play in driving this adjustment.trade collapse, multinational firms, global value chains, hierarchies of firms, vertical integration

Modeling measurement error via nonparametric Bayesian belief nets

Measurement error is the difference between the value provided by the respondent and the true (but unknown) value. It is sometimes defined as observation error, since it is related to the observation of the variable at the data collection stage. The problem of measurement error in financial assets is studied. The measurement error is modeled by means of non parametric Bayesian belief networks, that are graphical models expressing the dependence structure through bivariate copulas associated to the edges of the graph without introducing any distributional assumption. A new error correction procedure based on non parametric Bayesian belief networks is proposed. Measurement error modeling and microdata correction are illustrated by means of an application to the Banca d’Italia Survey on Household Income and Wealth 2008. The measurement model and its parameters have been estimated via a validation sample. The sensitivity of the conditional distribution of the true value given the observed one to different evidence configurations is analysed

Object-oriented Bayesian networks for combining several features of the quality

Customer orientation can be a strategic tool to support management decisions. Private companies and public authorities carry out customer satisfaction surveys to measure the perceived quality. The quality is a dynamic feature often interpreted as a mix of satisfaction items that can be analyzed both separately and jointly. Moreover, they can contribute to produce an index that synthesizes the hidden global quality. Here, we propose to combine several aspects of satisfaction using Object-Oriented Bayesian Networks.We present an application where each satisfaction area is modelled by a Bayesian network learnt from data; an Object-Oriented Bayesian network is built to handle the domain as a whole. The tool can then be used to evaluate improvement actions developed in one or more areas

Application of Bayesian networks in Official Statistics

In this paper recent results about the application of Bayesian networks to official statistics are presented. Bayesian networks are multivariate statistical models able to represent and manage complex dependence structures. Here they are proposed as a useful and unique framework by which it is possible to deal with many problems typical of survey data analysis. In particular here we focus on categorical variables and show how to derive classes of contingency table estimators in case of stratified sampling designs. Having this technology it becomes possible to perform poststratification, integration and missing data imputation. Furthermore we briefly discuss how to use Bayesian networks for decision as a support system to monitor and manage the data production process