Computational Statistics: Editorial

Editorial to the Special Issue on Interval Data Analysis of Computational Statistics Journa

A Study of the Conformers of the (Nonafluorobutanesulfonyl)imide Ion by Means of Infrared Spectroscopy and Density Functional Theory (DFT) Calculations

Pyrrolidinium-based ionic liquids with anions of the per(fluoroalkylsulfonyl)imide family are particularly interesting for their use as electrolytes in lithium batteries. These ions have several geometric isomers and the presence of different ion conformers and their distribution affects the ILs (Ionic liquids) physical and chemical properties. In the present work, we report the temperature dependence of the infrared spectra of the N-butyl-N-methyl-pyrrolidinium(trifluoromethanesulfonyl) (nonafluorobutanesulfonyl)imide (PYR14-IM14) ionic liquid; DFT (Density Functional Theory) calculations performed with different models provides indications about the IM14 conformers and their vibrational spectra. Moreover the temperature dependence of the intensity of the lines identified as markers of different conformers provide indications about the conformers’ distribution and the difference of their enthalpy in the liquid phase

An infrared spectroscopy study of the conformational evolution of the Bis(trifluoromethanesulfonyl)imide ion in the liquid and in the glass state

We measure the far-infrared spectrum of N,N-Dimethyl-N-ethyl-N-benzylammonium (DEBA) bis(trifluoromethanesulfonyl) imide (TFSI) ionic liquid (IL) in the temperature range between 160 and 307 K. Differential scanning calorimetry measurements indicate that such IL undergoes a glass transition around 210K. DFT calculations allow us to assign all the experimental absorptions to specific vibrations of the DEBA cation or of the two conformers of the TFSI anion. We find that the vibration frequencies calculated by means of the PBE0 functional are in better agreement with the experimental ones than those calculated at the B3LYP level, largely used for the attribution of vibration lines of ionic liquids. Experimentally we show that, in the liquid state, the relative concentrations of the two conformers of TFSI depend on temperature through the Boltzmann factor and the energy separation, ΔH, is found to be ≈2 kJ/mol, in agreement with previous calculations and literature. However, in the glassy state, the concentrations of the cis-TFSI and trans-TFSI remain fixed, witnessing the frozen state of this phase

Prototype definition through consensus analysis between fuzzy c-means and archetypal analysis

The general aim of cluster analysis is to build prototypes, or typologies of units that present similar characteristics. In this paper we propose an alternative approach based on consensus analysis of two different clustering methods to suitably obtain prototypes. The clustering methods used are fuzzy c-means (centre approach) and archetypal analysis (extreme approach). The consensus clustering is used to assess the correspondence between the clustering solutions obtained

Clustering mixed-type data using a probabilistic distance algorithm[Formula presented]

Cluster analysis is a broadly used unsupervised data analysis technique for finding groups of homogeneous units in a data set. Probabilistic distance clustering adjusted for cluster size (PDQ), discussed in this contribution, falls within the broad category of clustering methods initially developed to deal with continuous data; it has the advantage of fuzzy membership and robustness. However, a common issue in clustering deals with treating mixed-type data: continuous and categorical, which are among the most common types of data. This paper extends PDQ for mixed-type data using different dissimilarities for different kinds of variables. At first, the PDQ for mixed-type data is defined, then a simulation design shows its advantages compared to some state of the art techniques, and ultimately, it is used on a real data set. The conclusion includes some future developments

Chapter Clustering students according to their proficiency: a comparison between different approaches based on item response theory models

Evaluating learners' competencies is a crucial concern in education, and home and classroom structured tests represent an effective assessment tool. Structured tests consist of sets of items that can refer to several abilities or more than one topic. Several statistical approaches allow evaluating students considering the items in a multidimensional way, accounting for their structure. According to the evaluation's ending aim, the assessment process assigns a final grade to each student or clusters students in homogeneous groups according to their level of mastery and ability. The latter represents a helpful tool for developing tailored recommendations and remediations for each group. At this aim, latent class models represent a reference. In the item response theory (IRT) paradigm, the multidimensional latent class IRT models, releasing both the traditional constraints of unidimensionality and continuous nature of the latent trait, allow to detect sub-populations of homogeneous students according to their proficiency level also accounting for the multidimensional nature of their ability. Moreover, the semi-parametric formulation leads to several advantages in practice: It avoids normality assumptions that may not hold and reduces the computation demanding. This study compares the results of the multidimensional latent class IRT models with those obtained by a two-step procedure, which consists of firstly modeling a multidimensional IRT model to estimate students' ability and then applying a clustering algorithm to classify students accordingly. Regarding the latter, parametric and non-parametric approaches were considered. Data refer to the admission test for the degree course in psychology exploited in 2014 at the University of Naples Federico II. Students involved were N=944, and their ability dimensions were defined according to the domains assessed by the entrance exam, namely Humanities, Reading and Comprehension, Mathematics, Science, and English. In particular, a multidimensional two-parameter logistic IRT model for dichotomously-scored items was considered for students' ability estimation

A Computational and Experimental Study of the Conformers of Pyrrolidinium Ionic Liquid Cations Containing an Ethoxy Group in the Alkyl Side Chain

We investigate the conformers of the N-methoxyethyl-N-methylpyrrolidinium (PYR1(2O1)) and N-ethoxyethyl-Nmethylpyrrolidinium (PYR1(2O2)) ionic liquid cations by means of DFT calculations at the B3LYP/6-31G∗∗ level and we calculate their infrared vibration frequencies. The comparison with the absorbance spectra of two ionic liquids containing these ions indicates good performance of such a combination of theory and basis set.The lowest energy conformer of each pyrrolidinium cation displays equatorial-envelope geometry; however, in contrast with the prototypical PYR14, the main alkyl side chain is not in an all-trans configuration, but it tends to be bent. Moreover, calculations indicate that the LUMO orbital extends more along the alkyl side chain in PYR1(2O1) and PYR1(2O2) than in the parent ion 1-butyl-1-methylpyrrolidinium (PYR14)

A Regulatory Impact Analysis (RIA) approach based on evolutionary association patterns

The present paper focuses on ex post analysis to asses the impact of an adopted policy by measuring system performance. Since accurate impact assessment requires in-depth knowledge of the structure underlying the system, this contribution proposes a suitable use of multidimensional data analysis (MDA) to investigate the associations characterizing the indicators/attributes of the system. The general aim is to identify homogeneous subsets of objects that are described by subsets of attributes. This approach was planned to study students performance in Italian universities: the focus is on student careers. The example data set is a data mart selected from the University of Macerata data base and refers to the students at the Economics Faculty from 2001 to 2007

Young people's social agency and community action orientation: a partial least squares-path modeling approach using a self anchoring scale

In this paper we introduce the validation of a novel and specific indicator to measure social agency, namely Community Action Orientation (CAO). The study defines the CAO exploratory model as a second order Partial Least Squares-Path Model (PLSPM). The study identifies the latent variables of orientation toward the community selecting 14 items considered into three sets, suggesting how people invest in their local context on both a personal and collective level. Data have been collected through a self anchoring Cantril’s scale administered to 862 young people living in the administrative district of Naples. The exploratory analysis outcomes show a structure composed of three latent variables (dimensions), correlated with each other. We assumed that CAO is the endogenous variable in order to explain the agency of young individuals in their local context. To explain the interdependence among these latent variables, a theoretical model was hypothesized and constructed. Evidence of the use of the Cantril scale in conjunction with the PLS-PM corroborates the consistency of the approach