This paper investigates ESG from the perspective of changes in input elasticities substitution and complementarity. Rather than compute these cost function, we them Input Distance Function (IDF). Our data are Refinitiv Eikon Datastream database. We focus on US economy due to her global role world hence spillover effects uncertainties rest world. The consist 5,798 companies comprising 38 industr...

The purpose of this paper is to introduce a new estimation method for estimating the Archimedean copula dependence parameter in the non-parametric setting. The estimation of the dependence parameter has been selected as the value that minimizes the Cramér-von-Mises distance which measures the distance between Empirical Bernstein Kendall distribution function and true Kendall distribution functi...

We present an adaptive signed distance transform algorithm for curves in the plane. A hierarchy of bounding boxes is required for the input curves. We demonstrate the algorithm on the isocontours of a turbulence simulation. The algorithm provides guaranteed error bounds with a selective refinement approach. The domain over which the signed distance function is desired is adaptively triangulated...

The paper presents a method which shows a significant improvement in discovering the path over the distance vector protocol. The proposed method is a multi-parameter QoS along with the fitness function which shows that it overcomes the limitation of DV like routing loops by spanning tree approach, count-to-infinity problem by decision attribute. The input considered is a topology satisfying the...

UPPAAL/DMC is an extension of UPPAAL which provides generic heuristics for directed model checking. In this approach, the traversal of the state space is guided by a heuristic function which estimates the distance of a search state to the nearest error state. Our tool combines two recent approaches to design such estimation functions. Both are based on computing an abstraction of the system and...