Most of ex-ante impact assessment policy models have been based on a parametric approach. We develop a novel non-parametric approach, called Inverse DEA. We use non parametric efficiency analysis for determining the farm’s technology and behaviour. Then, we compare the parametric approach and the Inverse DEA models to a known data generating process. We use a bio-economic model as a data genera...

In recent years, developed societies have largely adopted smart systems operating on the basis of information extracted from data. For infrastructure systems as well, structural health monitoring (SHM) has long advocated a data-driven scheme for facilitating the operation and maintenance of infrastructure. In materializing such a goal, this paper demonstrates the procedures and outcomes of a SH...

We describe a new program lm_twoqtl, part of the MORGAN package, for parametric linkage analysis with a quantitative trait locus (QTL) model having one or two QTLs and a polygenic component, which models additional familial correlation from other unlinked QTLs. The program has no restriction on number of markers or complexity of pedigrees, facilitating use of more complex models with general pe...

Latent Class Analysis (LCA) is a statistical method used to identify subtypes of related cases using a set of categorical and/or continuous observed variables. Traditional LCA assumes that observations are independent. However, multilevel data structures are common in social and behavioral research and alternative strategies are needed. In this paper, a new methodology, multilevel latent class ...

In this work, we attempt to associate firm characteristics with innovative activity. We collect microdata from listed firms of selected Eurozone Country-members, after the beginning of 2007 financial crisis. The following literature, several indicators of growth and performance were selected and tested for their ability to interpret innovative activity. The main scope is to examine the possible...

Datasets with hundreds of variables and many missing values are commonplace. In this setting, it is both statistically and computationally challenging to detect true predictive relationships between variables and also to suppress false positives. This paper proposes an approach that combines probabilistic programming, information theory, and non-parametric Bayes. It shows how to use Bayesian no...

BACKGROUND The Occupational Health and Safety (OH&S) literature shows that noise could represent a risk factor for professional orchestral musicians. The continuative exposition to elevated noise levels and the particular nature of the activity make necessary an "atypical" OH&S approach, which was identified to be necessarily organizational. MATERIALS AND METHODS In this study, a parametric-b...

Quantifying the degree of spatial dependence for linguistic variables is a key task for analyzing dialectal variation. However, existing approaches have important drawbacks. First, they are based on parametric models of dependence, which limits their power in cases where the underlying parametric assumptions are violated. Second, they are not applicable to all types of linguistic data: some app...

In addressing the topic of decision making in the water sector, what has been suggested to be useful up to this point is benchmarking. This paper aims at exploring the relationship between the Operating Cost Coverage Index and customer complaints about water and wastewater services for 1898 water utilities in 11 countries, i.e., Australia, Bangladesh, Brazil, Lithuania, Peru, Poland, Russia, Se...

We study the determinants of common European merger policy over its first 25 years, from 1990 to 2014. Using a novel dataset at level relevant antitrust markets and containing all cases notified Commission, we evaluate how consistently arguments related structural market parameters – dominance, rising concentration, barriers entry, foreclosure were applied time across different geographic defin...