Early inference on reliability of upgraded automotive components by using past data and technical information

When a new product is the result of design and/or process improvements introduced in its predecessors, then the past failure data and the expert technical knowledge constitute a valuable source of information that can lead to a more accurate reliability estimate of the upgraded product. This paper proposes a Bayesian procedure to formalize the prior information available about the failure probability of an upgraded automotive component. The elicitation process makes use of the failure data of the past product, the designer information on the effectiveness of planned design/process modifications, information on actual working conditions of the upgraded component and, for outsourced components, technical knowledge on the effect of possible cost reductions. By using the proposed procedure, more accurate estimates of the failure probability can arise. The number of failed items in a future population of vehicles is also predicted to measure the effect of a possible extension of the warranty period. Finally, the proposed procedure was applied to a case study and its feasibility in supporting reliability estimation is illustrated.     

Correction to: Joint and conditional dependence modelling of peak district heating demand and outdoor temperature: a copula-based approach

Statistical Methods & Applications - This paper examines the complex dependence between peak district heating demand and outdoor temperature. Our aim is to provide the probability law of heat...     

Statistical matching and uncertainty analysis in combining household income and expenditure data

Among the goals of statistical matching, a very important one is the estimation of the joint distribution of variables not jointly observed in a sample survey but separately available from independent sample surveys. The absence of joint information on the variables of interest leads to uncertainty about the data generating model since the available sample information is unable to discriminate among a set of plausible joint distributions. In the present paper a short review of the concept of uncertainty in statistical matching under logical constraints, as well as how to measure uncertainty for continuous variables is presented. The notion of matching error is related to an appropriate measure of uncertainty and a criterion of selecting matching variables by choosing the variables minimizing such an uncertainty measure is introduced. Finally, a method to choose a plausible joint distribution for the variables of interest via iterative proportional fitting algorithm is described. The proposed methodology is then applied to household income and expenditure data when extra sample information regarding the average propensity to consume is available. This leads to a reconstructed complete dataset where each record includes measures on income and expenditure.     

Urban poverty and labor market dynamics in five Latin American countries: 2003–2008

Latin America experienced a long period of sustained growth since 2003 that positively impacted social and labor market indicators, including poverty. This paper contributes to the understanding of this process as it carries out a comparative study of poverty dynamics in five Latin American countries during 2003–2008. It analyzes the extent to which countries with different levels of poverty incidence diverge in terms of poverty exit and entry rates, identifies the relative importance of the frequency and impact of events associated to poverty transitions and examines how these events affect households with different characteristics. For this, a dynamic analysis of panel data is carried out using regular household surveys. Sizeable rates of poverty movements were observed in all five countries and it was found that a large proportion of household experienced positive events, mainly related to the labor market; however, only a small fraction of them actually exited poverty. Demographic events and public cash transfers proved to be of little relevance; in particular, the latter did not contribute much either to intensify poverty exits or to prevent poverty entries. Households with children experienced more (less) negative (positive) events than those without children. It appeared therefore that even when the economy behaved reasonably well at the aggregate level, high levels of labor turnover and income mobility (even of a negative nature) still prevail, mainly associated to the high level of precariousness and the undeveloped system of social protection that characterize the studied countries.     

Soziologische Theorie, Methoden, Migrationssoziologie, Arbeitssoziologie, Wirtschaftssoziologie, Mitbestimmung, Umweltsoziologie

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Soziologische Theorie, Methoden, Migrationssoziologie, Arbeitssoziologie, Wirtschaftssoziologie, Mitbestimmung, Umweltsoziologie     

Social context,spatial structure and social network structure

Frequently, social networks are studied in their own right with analyses devoid of contextual details. Yet contextual features – both social and spatial – can have impacts on the networks formed within them. This idea is explored with five empirical networks representing different contexts and the use of distinct modeling strategies. These strategies include network visualizations, QAP regression, exponential random graph models, blockmodeling and a combination of blockmodels with exponential random graph models within a single framework. We start with two empirical examples of networks inside organizations. The familiar Bank Wiring Room data show that the social organization (social context) and spatial arrangement of the room help account for the social relations formed there. The second example comes from a police academy where two designed arrangements, one social and one spatial, powerfully determine the relational social structures formed by recruits. The next example is an inter-organizational network that emerged as part of a response to a natural disaster where features of the improvised context helped account for the relations that formed between organizations participating in the search and rescue mission. We then consider an anthropological example of signed relations among sub-tribes in the New Guinea highlands where the physical geography is fixed. This is followed by a trading network off the Dalmatian coast where geography and physical conditions matter. Through these examples, we show that context matters by shaping the structure of networks that form and that a variety of network analytic tools can be mobilized to reveal how networks are shaped, in part, by social and spatial contexts. Implications for studying social networks are suggested.