Miriam Esteve

Universidad Miguel Hernández de Elche | UMH · Centro de Investigación Operativa

In this paper, we introduce a new methodology based on regression trees for estimating production frontiers satisfying fundamental postulates of microeconomics, such as free disposability. This new approach, baptized as Efficiency Analysis Trees (EAT), shares some similarities with the Free Disposal Hull (FDH) technique. However, and in contrast to...

In the literature of Economics, Engineering and Operations Research, the estimation of production frontiers is a current hot topic. Many parametric and nonparametric methodologies have been introduced for estimating technical efficiency of a set of units (for example, firms) from the production frontier. However, few of these methodologies are base...

The determination of technical efficiency through the previous estimation of a production frontier has been a relevant topic in the literature related to production theory and engineering. Many parametric and nonparametric approaches have been introduced in the last forty years for estimating production frontiers given a data sample. However, few o...

This is the package of R created for estimating technical efficiency improving FDH and DEA. The new technique, called EAT (Efficiency Analysis Trees), avoids the problem of overfitting associated with the standard non-parametric methodologies. We show how to use the package through some numerical examples. This is related to our objective of creati...

eat is a new package for R that includes functions to estimate production frontiers and technical efficiency measures through non-parametric techniques based upon regression trees. The package specifically implements the main algorithms associated with a recently introduced methodology for estimating the efficiency of a set of decision-making units...

In the technical efficiency evaluation area, it may happen that many observations obtain a similar relative technical efficiency status, making it difficult to discriminate between them. The determination of super-efficiency has been a way of solving this problem by providing a method to differentiate between the performance of observations. Despit...

This chapter introduces Conjunctive Analysis of Case Configurations (CACC) for the study of crime and place. After introducing CACC as an alternative approach to variable-oriented thinking, we present its conceptual underpinnings and limitations. We then provide a step-by-step tutorial on how to conduct a CACC, accompanied by an example using publi...

The continuous input of data into an Information System makes it difficult to generate a reliable model when this stream changes unpredictably. This continuous and unexpected change of data, known as concept drift, is faced by different strategies depending on its type. Several contributions are focused on the adaptations of traditional Machine Lea...

This R package contains a set of functions to conduct a Conjunctive Analysis of Case Configurations (CACC; Miethe, Hart & Regoeczi, 2008). “cacc” is the first and foremost function. This function collects a data frame to execute a CACC. As a result, it returns another data frame that contains only the dominant profiles observed in the data, the n...

The online social network Twitter, apart from being one of the main vehicles of communication in the cyberspace, has become an effective diffusor of fear of crime. The latter phenomenon has caught the attention of researchers since the 1960’s, amongst other reasons due to the impact on the citizens’ quality of life and consequently the call for its...

Fear of crime has been one of the most compelling scientific phenomena since the 60s. Its scope has traditionally been limited to assess this emotional experience predominantly in physical space. However, studies on fear of crime experiences are gradually increasing in this new area of criminal opportunity, which is cyberspace. The aim of this pape...

Abstract With the objective of facilitating and reducing analysis tasks undergone by law enforcement agencies and service providers, and using a sample of digital messages (i.e., tweets) sent via Twitter following the June 2017 London Bridge terror attack (N = 200,880), the present study introduces a new algorithm designed to detect hate speech mes...

The sharp rise in social networks in any field of opinion has led to the increasing importance of content analysis. Due to the concretion of the texts published on Twitter from its limitation to 140 characters, this network is the most suitable for the analysis and classification of opinions according to different criteria. Therefore, there are mul...