Empirical Applications of Multidimensional Inequality Analysis

This paper explores the empirical application of theoretical multidimensional inequality analysis using real household welfare distributions. The paper operationalises recent conceptual developments in multidimensional inequality theory and assesses their usefulness for measurement and policy analysis. Despite the existence of a thriving theoretical literature on multidimensional inequality, empirical applications, particularly at the individual and household levels, are few and far between. This paper compares and contrasts different methodologies for the analysis of multidimensional welfare, including multidimensional inequality indices and stochastic dominance techniques. The results strongly highlight the importance of bringing non-monetary aspects of household welfare into the forefront of inequality analysis since measurements based solely on the distribution of income variables may misrepresent the degree of overall inequality in society. Agreement over the various approaches to the measurement of multidimensional inequality entails, however, non-trivial decisions that may limit the practical usefulness of these measures. We suggest that the use of multidimensional inequality ranges and restrictive dominance criteria may open significant scope for further developments in the empirical analysis of multidimensional inequality.Multidimensional inequality; inequality indices; income inequality; education inequality; health inequality; stochastic dominance

A comparison of two techniques for bibliometric mapping: Multidimensional scaling and VOS

VOS is a new mapping technique that can serve as an alternative to the well-known technique of multidimensional scaling. We present an extensive comparison between the use of multidimensional scaling and the use of VOS for constructing bibliometric maps. In our theoretical analysis, we show the mathematical relation between the two techniques. In our experimental analysis, we use the techniques for constructing maps of authors, journals, and keywords. Two commonly used approaches to bibliometric mapping, both based on multidimensional scaling, turn out to produce maps that suffer from artifacts. Maps constructed using VOS turn out not to have this problem. We conclude that in general maps constructed using VOS provide a more satisfactory representation of a data set than maps constructed using well-known multidimensional scaling approaches

AMADA-Analysis of Multidimensional Astronomical Datasets

We present AMADA, an interactive web application to analyse multidimensional datasets. The user uploads a simple ASCII file and AMADA performs a number of exploratory analysis together with contemporary visualizations diagnostics. The package performs a hierarchical clustering in the parameter space, and the user can choose among linear, monotonic or non-linear correlation analysis. AMADA provides a number of clustering visualization diagnostics such as heatmaps, dendrograms, chord diagrams, and graphs. In addition, AMADA has the option to run a standard or robust principal components analysis, displaying the results as polar bar plots. The code is written in R and the web interface was created using the Shiny framework. AMADA source-code is freely available at https://goo.gl/KeSPue, and the shiny-app at http://goo.gl/UTnU7I.Comment: Accepted for publication in Astronomy & Computin

Point Information Gain and Multidimensional Data Analysis

We generalize the Point information gain (PIG) and derived quantities, i.e. Point information entropy (PIE) and Point information entropy density (PIED), for the case of R\'enyi entropy and simulate the behavior of PIG for typical distributions. We also use these methods for the analysis of multidimensional datasets. We demonstrate the main properties of PIE/PIED spectra for the real data on the example of several images, and discuss possible further utilization in other fields of data processing.Comment: 16 pages, 6 figure

THE DESIGN AND IMPLEMENTATION OF OLAP SYSTEM. CASE STUDY – UNIVERSITY RESEARCH

The aim of this study is to show that multidimensional modelling of existing data in organizations, depending on the topics of interest of managers and multidimensional view of data. It may also provide an effective informational support of managers in decision making, regardless of field of activity. To prove it, this study will design a data model and an OLAP multidimensional analysis of scientific research in education university.OLAP, hyper - cube, n-dimensional cube, conceptual model

Comparing Multidimensional Poverty between Egypt and Tunisia

It is common to argue that poverty is a multidimensional issue. Yet few studies have included the various dimensions of deprivation to yield a broader and fuller picture of poverty. The present paper considers the multidimensional aspects of deprivation by specifying a poverty line for each aspect and combines their associated one-dimensional poverty-gaps into multidimensional poverty measures. An application of these measures to compare poverty between Egypt and Tunisia is illustrated using robustness analysis and household data from each country.Multidimensional poverty indices, Robustness analysis, Egypt, Tunisia

Lie Symmetry Methods for Multidimensional Linear, Parabolic PDES and Diffusions

In this paper we introduce methods based upon Lie symmetry analysis for the construction of explicit fundamental solutions of multidimensional parabolic PDEs. We give applications to the problem of finding transition probability densities for multidimensional diffusions and to representation theory.Lie symmetry groups; fundamental solutions; transition densities; representation theory